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Internet of Things is a buzzword that is trained to blend itself in today's market seamlessly. But do you know what it is? Also, what does it signify for the delivery sector? IoT mainly refers to the concept of connecting various devices and transferring data using wireless apps. It eliminates face-to-face human interaction to a great extent.

The Internet of Things guarantees big things in the world of customer goods, but even more significant things in the evolution of the supply chain. Research firm Gartner stated that IoT would change the world of delivery services. A thirty-fold increase in Internet-connected physical machines by 2020 will significantly alter how the sector works. Morgan Stanley concludes that 75 billion devices will be connected with IoT-enabled devices by the end of 2020.

With today's growing customer demands for personalized and speedy service, it's no surprise IoT is evolving rapidly; this is special for the delivery and logistics sector. With IoT becoming more accepted globally, more devices are designed with sensors that can be monitored, opening up countless opportunities for those that choose to board the growing trend. With the advanced technology to carve a position in the delivery market, it's fascinating to keep an eye on how the sector ecosystem transforms and the type effects on system and operations.

Food Delivery with IoT: Explore How it Enhances Business Operations!

The IoT is quickly widespread in the food delivery sector. It has been primarily driven by pizza chains, including Pizza Hut, Dominos, and many more. Using smart devices, a customer can easily order mouth-watering pizza, get an estimated time for delivery, get a real-time update, watch the order being made through a webcam, etc.

Delivery personnel if knowing the exact delivery location can eliminate time lost to confusing addresses. Tipping and payment can also be handled through feature-rich solutions, making the process more efficient. The best part is that delivery brands like UberEats are leveraging the advantage of IoT technology.

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MarketsandMarkets determined the global IoT market size is valued at 170.6 billion in 2017. It's presumed to reach 561.0 billion by the end of 2022, at a 26.9% Compound Annual Growth Rate during the predicted period. The report scope covers the internet of things market by platform, software solution, services, apps region, and area.

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Image: (Source)

The software solution is divided into remote monitoring, real-time streaming analytics, data management, network bandwidth management, and security solution. However, it's further segmented into developing home automation, smart manufacturing, energy, retail, mobility, and transportation.

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Image: (Source)

The simple deployment and low-cost process of IoT-powered devices mean virtually any restaurant service that can provide smart delivery. However, numerous restaurants, including local chains, are lacking to take advantage of and opportunities IoT provides to them. A restaurateur can provide turnkey with smart IoT-enabled solutions, helping to complete and manage every business operation effectively.

Impact of IoT On Delivery Industry

With ever-growing customer demands for personalized and speedy service, it is no wonder the IoT is increasing, especially in the logistics and delivery sector. However, the IoT will allow troubleshooting and greater accuracy throughout the fully automated methods, significantly reducing the brand's required work hours.

With IoT existing is accepted globally, more devices are developing with sensors that can be tracked, thereby opening up countless opportunities. Machine-to-Machine and IoT interaction are evolving customer expectations around the delivery sector, forcing providers to replan and know how they can do more business and generate more leads in less time.

Increases Operational Visibility

In the delivery sector, operational visibility is critical for developing faster and more efficient actions. Luckily improved visibility is the primary benefit the IoT technology brings to your table. The restaurateur can obtain valuable insight into accurate data-driven decisions and operations.

Building a well-integrated IoT platform at your place can provide the fleet manager with information and a deeper understanding of data like on-time deliveries, real-time alerts, and more. All the data provided by managers possess the ability to decrease unnecessary problems that can otherwise arise. In simple terms, an IoT system permits data-driven judgments to occur and reduces unexpected problems; all this reduces extra cost throughout the delivery process.

Moreover, in terms of warehouse services, IoT streamlines operations with sensors, bar code readers, etc., ensuring to provide you with visibility of inventory and tracing of products and services quickly and efficiently. In essence, business managers can easily understand what products they have to make snap decisions accordingly.

Route Optimisation

Visibility is critical for delivery brands wishing to thrive in a competitive market, but it's not only one factor why brands must consider IoT integration. Inefficient and unorganized routes can result in a downfall; such routes increase fuel use, road time, carbon footprints, and other resources. However, this dramatically affects the company's bottom line as well as the operational environment.

However, IoT-enabled devices are fighting all of this by strategically utilizing corporation resources to relinquish all planned destinations and open interaction between fleet managers and drivers. It improves real-time analytics and helps to achieve an efficient system of operations and manage consumer satisfaction.

Improves Real-Time Tracking

Every delivery business understands the stress of managing multiple deliveries at a time. However, a restaurateur can develop food delivery apps using IoT technology, helping them to stay aware of the real-time location of drivers and deliveries. It helps them to deal with unexpected problems that sometimes occur on the road.

The data enables restaurateurs to drive accurate and intelligent decision-making, ensuring to improve customer service by keeping customers updated about the delivery service. Most brands these days are using RFID and are approaching about 100% receiving accuracy, 33% faster order processing whereas 30% reduction in operational costs."

Efficient Last-Mile Delivery

Due to customer demand and delivery growth, many complex challenges are created for a restaurateur to tackle. Most of the challenges arise due to last-mile delivery due to driver behavior, traffic, driver behavior, etc. However, IoT is helping supermarkets and restaurants at every stage, helping them replan their operation process and ensure a streamlined journey for customers.

Hence restaurateur needs to find a cost-effective platform that satisfies customer needs and unexpected problems. Modern technology enables them to bridge the gap between customers and driver inter-communication, ensuring business growth.

Preventive Maintenance

Additionally, if you want to gain better insight into delivery provider behavior, you can connect all your vehicles. It even helps with preventive maintenance for the vehicle. IoT-connected vehicles will send automated signals and warning alerts when any part of a particular vehicle requires maintenance. 

With the help of such alters, you can easily maintain services such as a low battery, coolant temperature, check engine, etc., ensuring to leverage preventive maintenance and increasing the lifespan of your vehicles.

Wrapping It Up

The delivery sector is experiencing a lot of change with the IoT, and it seems to have more improvements shortly as well. The advantages of IoT in the delivery industry are indisputable, and as more and more devices are connected, further optimizations show that the numbers will grow. 

The urgency of IoT adoption differs from one sector to another and its impact as well. But it has excellent benefits for the delivery sector as it provides excellent visibility, reduces operation cost, and better last-mile execution. Hence considering integrating IoT within your business process is a wise choice that will bring worth for your business.

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Happy Friday (or whatever day it is when you find yourself reading this). I’m currently bouncing off the walls in excitement because I’ve been invited to host a panel discussion as part of a webinar series — Fast and Fearless: The Future of IoT Software Development — being held under the august auspices of IoTCentral.io

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Panel members Joe Alderson (upper left), Pamela Cortez (upper right), Katherine Scott (lower left), and Ihor Dvoretskyi (bottom right)

At this event, the first of a 4-part series, we will be focusing on “The IoT Software Developer Experience.”

As we all know, the IoT is transforming the software landscape. What used to be a relatively straightforward embedded software stack has been revolutionized by the IoT, with developers now having to juggle specialized workloads, security, machine learning, real-time connectivity, managing devices that have been deployed into the field… the list goes on.

In this webinar — which will be held on Tuesday 11 May 2021 from 10:00 a.m. to 11:00 a.m. CDT — I will be joined by four industry luminaries to discuss the development challenges engineers are facing today, how the industry is helping to make IoT development easier, an overview of development processes (including cloud-based continuous integration (CI) workflows and low-code development), and what the future looks like for developers who are building for the IoT. 

The luminaries in question (and whom I will be questioning) are Joe Alderson (Director of Embedded Tools and User Experience at Arm), Pamela Cortez (IoT Developer Advocate and Sr. Program Manager at Microsoft Azure IoT), Katherine Scott, Developer Advocate at Open Robotics, and Ihor Dvoretskyi (Developer Advocate at Cloud Native Computing Foundation).

So, what say you? Dare I hope that we will have the pleasure of your company and that you will be able to join us to (a) tease your auditory input systems with our discussions and (b) join our question-and-answer free-for-all at the end?

Recording available:

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Well, this isn’t something I expected to be talking about today, but my chum Ben Cook just introduced me to something that looks rather cool.

Ben is the Founder and Director at Airspeed Electronics Ltd., which is an electronic design consultancy that’s based in the UK specializing in high-performance acoustic detection and tracking technology for counter-unmanned aircraft system (UAS) applications. The folks at Airspeed Electronics are currently developing a drone detection and tracking system called MANTIS, where this work is being funded through a research grant provided by the UK Ministry of Defence (which — before you make a nasty comment — is how they spell “Defense” in the UK).

MANTIS, which stands for “MAchine learNing acousTIc Surveillance,” is a system of distributed, intelligent acoustic sensors that use artificial intelligence (AI) for the detection, classification, and location estimation of UAS — such as drones — based on their acoustic signatures.

But that’s not what I wanted to talk to you about…

In his email to me, Ben spake as follows: “Have you heard of an embedded operating system called ‘Luos’ before? It’s a microservices software architecture, like docker but for use with microcontrollers. I have no affiliation, I just stumbled across this today and I’m thinking this could be very useful for some future projects. It looks really good for anything ‘modular-y,’ if you know what I mean…”

I do know what Ben means. I just meandered my way around the luos.io website, perused and pondered the documentation at docs.luos.io, and watched this video on YouTube (later today, I’m going to get the tattoo, buy the T-shirt, and see the stage play).

In a nutshell, Luos is a simple and lightweight open-source distributed operating system dedicated to embedded systems. It uses the concept of modularity to simplify the linking of components and chunks of application code together to form a single system image.

Consider a system like a robot that uses multiple microcontrollers to manage its various sensors, actuators, and motors. If each of these microcontrollers employs Luos technology, all of them can use any feature of any microcontroller in the system as if all of the features were located in the same component.

Now, I’m a hardware design engineer by trade, so the software side is a bit outside my bailiwick, but — even so — looking at the video above and scanning the documentation makes me sit up and say, “Wow, this looks really, really cool.”

I asked around a few of my embedded systems software developer friends, and no one had heard of Luos, but I have a feeling that this may be a tool that’s poised to make a big splash. All sorts of ideas are currently bouncing around my head, like the fact that the Tracealyzer tool from Percepio would make an ideal companion for the Luos OS (see also The 2021 Embedded Online Conference Approacheth).

How about you? Have you heard of Luos? If so, what are your thoughts? If not, and if you lean toward the software side of things, it would be great if you could take a look with your highly trained eye, see what you think, and report back to the rest of us in the comments below.

Originally posted HERE

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In the age of next-generation computer, the role of the cloud, the internet and smart devices will become stronger. These days we all know the word smart well. This word is often used in our daily lives. The Internet of Things (IoT) will generate a variety of information from a variety of resources. It can store big data in the cloud. Fog computing acts as a signal between cloud and IoT. Fog extensions in this framework apply to material under IoT. IoT devices are called Fog nodes, which can be accessed anywhere within the network range. A blockchain is a novel way of recording in a secure sequence. Creating a new framework in the development of Internet of Things is one of the critical problems of wireless communication where solving such a problem can lead to continued growth in the use and popularity of IoT. Proposed research creates a framework for providing a framework for middleware on the internet of smart devices network for the internet of things using blockchains technology. Our great offering connects new research that integrates blockchains into the Internet of Things and provides secure Internet connection for smart devices. Blockchain (BC) Internet of Things (IoT) is a new technology that works with low-level, distributed, public and real-time leaders to maintain transactions between IoT sites. A blockchain is a series of blocks, each block being linked to its previous blocks. All blocks have cryptographic hash code, previous block hash, and its data. Transactions in BC are the basic components used to transfer data between IoT nodes. IoT nodes are a variety of portable but smart devices with embedded sensors, actuators, systems and the ability to communicate with other IoT nodes. The role of BC in IoT is to provide a process for processing secure data records using IoT nodes. BC is a protected technology that can be used publicly and openly. IoT requires this type of technology to allow secure communication between IoT nodes in different environments. Events in BC can be tracked and monitored by anyone who is certified to communicate within IoT.

 Index Terms—Blockchain, Internet of Things, Security, Privacy, Wireless Communication.

1. INTRODUCTION

The proposed framework introduces and presents its role in IoT. The IoT-Fog framework has the following features:He IoT is growing exponentially year by year with its focus on 5G technologies, such as Smart Homes and Cities, Health, intelligence surveillance etc. But there are challenges to security and privacy. IoT devices are connected in a shared power. Therefore, it is very complicated to use the most common security methods available for communication between IoT nodes. The proposed research is a step forward in wireless communication with IoT where we propose a new middleware framework based on blockchain technology. Wireless communication is the Internet key for things. It is expected to exceed 50 billion connected devices by 2020 and most of these nodes cannot be connected via wireline. In order to enable critical systems such as intelligent industries or intelligent structures, communication processes must address the ambiguous nature of wireless links. The research work proposed in this project is to develop and implement a middleware framework based on blockchain technology in the construction of the Internet of Things. The result of the research is to establish a new IoT framework. The proposed research uses the correct and effective imitation of the study you are looking for and can be done through the Internet of Things. In the future, researchers could expand this research and use it online for everything. Creating a new middleware-based block ware framework in the development of Internet of Things can be an important framework for improving the performance of the IoT framework in a unique environment. Wireless communication is a fast-growing research area that enables users to interact without using cables. Internet of Things is based on a completely wireless network. At the beginning of the Internet, it was developed to communicate from one device to another using access to browsers. However, in the modern era, high-performance high-speed devices have many advanced technologies such as low power consumption etc. Available to communicate with others. Fog extensions in this framework apply to material under IoT. IoT devices are called Fog nodes, which can be accessed anywhere within the network range. This research will help the IoT framework. However, the analysis framework is studied in the literature review, the authors did not describe the full framework in this study. This study adds a blockchain and an advanced fog to improve the effective IoT framework for communication between smart devices. Comparisons of this study with the limitations of the re-examination of previous research, admissions, bulk variations and poor distribution of production packages are mandatory. The algorithm was used for testing. The proposed framework accurately predicts our comprehensive assessment. In addition, confirm the results of the statistics. The purpose of this study is to create a new model of communication between the Internet of Things and Fog computing. This research is based on blockchain technology with Middleware, Fog, and IoT. The main contribution of this study is to design an Internet communication framework using fog and blockchain technology. The proposed framework is specifically suited for applications where data is periodically transferred to the natural network of smart devices. In these applications, on the other hand, packets are produced based on a specific time pattern. On the other hand, service time is constantly changing randomly with standard distribution. Therefore, the service time may be temporarily delayed, as an inevitable result some packages may encounter a busy channel and be discarded. We solve this problem by proposing a new middleware framework. We show that the proposed IoT-Fog framework, not only increases inputs, but also direct connections between generations (sensors) and communication packet systems are removed which makes the system more stable. In addition, in order to improve the proposed model, we have hired a redistribution system, flexible pack length, and full vehicle condition. The solution to this study is summarized as follows. The implementation of the IoT-Fog framework for internet connectivity for 5G smart devices will be set to work online for things. The concept will work with a three-layer model, these layers are Fog, Blockchain and IoT. The proposed research supports wireless communication technology to establish the IoT-Fog framework within the network of device devices.

  1. a) Devices (Items)
  2. b) The Internet
  3. c) Middleware
  4. d) Using fog with blockchain

In fog, status servers store secure resources, proxies by third-party servers can store protected data and owners are legitimate devices. The key server in middleware creates encryption keys. A token given to a smart device by an authorized blockchains database has the authority to access the framework, request keys from the key server, and download data to the cloud. Figure 1 presents the components of the proposed framework.

 The The following steps are applied to the proposed framework.

  1. Smart contracts published by status servers, attorneys and fog owners in an authorized database of blockchains.
  2. IoT smart device detects smart contacts from authorized database of blockchains.
  3. An authorized blockchains database archive creates an intelligent IoT device token.
  4. The smart device asks for the keys from the key server in the middleware and sends the token with the application.
  5. Key server in middleware verify the token from the authorized blockchain database and create a smart device key and feedback back to the smart device.
  6. Now the smart IoT device is authorized to access data from the cloud.

The framework itself is divided into three layers: IoT device layer, Fog layer, and cloud layer.

The framework can provide QoS by reducing traffic congestion and variability in the number of smart devices. In this study, we look at the state of inactivity in order to make our tests more effective, at which point, the general performance regarding the overall performance of the framework is assessed. IoT-Fog in this framework will view and analyze real-time data collected on fog nodes and take action.

The following are the key points-

  1. The study is mainly focused on IoT. Enables smart devices to communicate with another device within the Internet of smart devices using blockchain technology.
  2. The proposed communication framework will access the internet for smart devices.
  3. The results of the proposed study will be compared with the previous study in the same area.

2. BACKGROUND

In 1991, Theodore S. Rappaport published an article entitled “The Wireless Revolution”, in which he introduced wireless communication technology as the key to communication between people as well as devices. In 1994, Andy Harter and Andy Hopper published an article entitled “A Distributed Location System for the Active Office”, in this paper, outlining infrared sensor arrangements using communication badges between devices and workstations. In 1994, Tristan Richardson, Frazer Bennett, Glenford Mapp, and Andy Hopper presented the article “A ubiquitous, personalized computer Telephony in the X Window System Environment”, in this article they introduced X windows, X programs protocol for securing communication between client and server. In the article, the authors represented the "System Software for Ubiquitous Computing" for the integration of different types of networks, and created connections between devices on different types of networks. In 2002 the researchers published an article entitled “Connecting the Physical World with Pervasive Networks”, in which they addressed the challenges and opportunities of using the physical world through widespread compte-rich computation networks. Cloud computing came as a result of the continued development of computer paradigms. The advent of this technology has created the emergence of software (SaaS) as a service that says consumers do not need to buy software rather than go according to their needs. In 2006, Amazon achieved a milestone by testing the elastic elastic computing cloud (EC 2) that started the computer. * However, the term cloud computing did not coincide until March 2007. The following year saw the rapid development of this new system. In addition, cloud infrastructure services have expanded to install software (SaaS) as a service. In mid-2012, Oracle's cloud was introduced, which supports a wide range of deployments. For example, it could lead to more than 139,000,000 games on Google In May 2014, Lihong Jiang et al published an article entitled "An IoT-Oriented Data Storage Framework in Cloud Computing Platform", focusing on the framework storage of relevant data allow not only to properly store large IoT data, but also to integrate both scheduled unstructured data. In this article, the IoT biological system and key technologies to support IoT communication are introduced. In 2016, Maria Rita Palattella et al published an article entitled "Internet of Things in the 5G Era: Enablers, Architecture and Business Models", in this article they introduced IoT 5G technology, exploring both technological aspects and standards. In 2018, Pradip Kumar Sharma, Yen Chen and Jong Hyuk Par published an article entitled, "Software Defined Fog Node Based Distributed Blockchain Cloud Architecture IoT". They introduced the software-defined environment using the IoT blockchain cloud.

 Building a new reliable framework based on IEEE 802.15.4 online communication for smart devices can be an important framework for improving the reliability of communication. Wireless networks enable users to interact with each other in the IoT environment. But there are many challenges to secure and reliable communication. Early in the Internet, It was developed to connect one device to another device using browser access. However, in the modern era, high-performance devices have many advanced technologies such as low power consumption etc. Available to communicate with others. Communication reliability has been suggested as one of the most important issues for wireless communication where solving such a problem can lead to continued growth in IoT use and popularity. The proposed research creates a framework to provide internet connectivity for the network of smart devices for the internet of things using IEEE802.15.4. Our great offering connects new research that combines reliability in the Internet of Things and provides reliable online connectivity for smart devices. This research will help the IoT framework. However, the analytical framework is read in book reviews, the authors did not describe the full framework in their essays. This study adds an improved Markov-chain and MAC framework to improve the effective framework of communication between smart devices. Comparisons of this study with the limitations of the re-examination of previous research, validation, bulk variability and poor distribution of production packages are mandatory. The algorithm was used for testing. The proposed framework accurately predicts our comprehensive assessment. In addition, the imitation of Monte-Carlo confirms the mathematical results. Smart devices are growing increasingly day by day around the world. They offer a lot of services to end users and attach to their daily lives. Smart devices can easily connect to the Internet by sending and receiving data within a network. Smart devices are not just Smartphones, it can be a smart refrigerator, Smart home entry, smart air conditioners, Smart hubs, Smart thermostat, Color changing LED smartphones, Smart Watches and tablets smart etc in the online framework of things, connected to each other via the internet.

TABLE 1: IoT Devices installed category and year wise (in Millions) 

Category

2016

2017

2018

2020

IoT Devices

3963.0

5244.3

7036.3

12863.0

Business: Across Industries

1102.1

1501.0

2132.6

4381.4

Business: Vertical specific

1316.6

1635.4

2027.7

3171.0

Total

6381.8

8380.6

11196.6

20415.4

 

The The proposed research program creates research to facilitate online communication of objects using fog technology and blockchain. Transferring data from one configuration to another using a wireless network dates back to 1973 in the form of radio network packets. They were able to communicate with other similar configuration devices. Recent work is underway on a project called Serval Project. Provides networking location for Android communication devices on a sub-network. While our research is concerned with the online connection of objects. The main contribution of this study is the construction of a communication framework and provide reliable and fast communication using fog and blockchain between the internet of smart devices. Previous studies have focused on building and utilizing a communication framework, but such research does not create a complete framework for IoT-Fog communication between the internet of smart devices.

BC is a technology that provides transaction security between IoT devices. Provides shared, distributed and publicly available shared leagues to store used blockchain data and authentication on the IoT network. Information stored in a public ledger is automatically managed using a peer-to-peer topology. BC is a technology in which transactions are drawn in the form of a block in BC between IoT nodes. Blocks are connected and all devices have the device's previous address. Blockchain and IoT together work in the framework of IoT and Cloud integration. In the future, BC will alter IoT interactions [1]. The objectives for the integration of BC and IoT can be summarized as follows.

  1.  Distributed framework: This method is similar to IoT and BC. It is removed from one system and provide location for the program in the field. It improves the chances of failure and performance of the entire system.
  2. Security: In BC, transactions between nodes are secure. It is a novel way of secure communication. BC allows IoT devices to communicate securely.
  3. Identification: In IoT, all connected devices are identified separately with a unique ID. All BC blocks are also identified separately. Therefore, BC is a reliable technology that provides specially identified information stored in public records.
  4. Reliability: IoT sites in BC have the ability to verify information transmitted over a network. The details are reliable because they were verified by the miners before entering BC. Only verified blocks can enter BC.
  5. Independence: In BC, all IoT nodes are free to connect to any node in a network without an intermediate system.
  6. Variety: In BC, IoT devices will communicate widely available, a distributed intelligence network that connects to the destination device in real time and with exchange details.

The other paper is summarized as follows: section 1 represents the presentation of the paper, section 2 represents the literature review, section 3 introduces the role of BC in IoT, section 4 represents the possibilities of an integrated approach, section 5 represents the challenges and section 6 represents the conclusion.

Security and privacy in communication between IoT devices are of paramount importance in 2017 and 2018. Several papers were published in 2017 and 2018. In 1990, Stuart Haber and W. Scott Stornetta wrote the article [3] in exchange for document and privacy without retaining any information about the punctuation service. The concept of blockchains comes from [3] but the first blockchains were introduced by Satoshi Nakamoto in 2008. He presented a paper in which blocks were chained together forming a blockchain [4]. In the article [5], the authors introduced "IoTChain" to verify the information exchanged between the two sites in the IoT network. They introduced an algorithm for exchanging data on IoT and blockchains (fig. 2) [5]. In this paper, the authors focus on the security component of the IoTChain framework.

 In the article [6], the authors explored the cloud and the MANN framework to connect smart devices to the internet of objects and provide communication security. In the article [7], the authors represent an excellent framework called an internet-cloud framework, it is a good idea to provide secure connections to IoT devices. In the article [8], the authors provide a framework for middleware in the construction of MANET cloud access to data between IoT devices. Article [9,10] represents fidelity in communication between IoT nodes. Articles [11,12,13,14,15] provide mobile mobility models for 5G networks. In the article [16], a travel framework is defined based on the understanding of communication security. In the article [17], a positive study on blockchains and IoT was conducted by researchers. They introduced the security concept to BC-IoT to improve IoT applications with the power of BCs.

3. THE ROLE OF BC IN IoT

 IoT enables visual cables to exchange their data over a different network [18]. IoT can be divided into the following categories.

  1. Physical Objects: IoT provides a unique id of each object connected to the network. Material is able to exchange data with other IoT nodes.
  2. Gates: Device gates work between material and cloud to ensure that communication is established, and security is provided by the network.
  3. Connectivity: used to control data flow and establish a very short route between IoT sites.
  4. Cloud: Used to store and count data.

BC is a series of verified blocks and those of encrypted encryption held by a network-connected device. Block data is stored in a publicly shared and distributed digital ledge. BC provides secure connection to the IoT network. A blockchain can be a private, public or consortium with a variety of structures. The following table represents the differences between all types of blockchains.

Table 2 : Kinds of Blockchains and their properties 

BC/ Properties

Efficiency

Decentralized

Accord growth

immovableness

Reading

Determining

Private BC

good

No

yes

Can be

Can be publicly

Only one industry

Public BC

worse

Yes

no

No

publicly

All miners

Consortium BC

good

Sometimes

yes

Can be

Can be publicly

IoT devices

 

The database in blockchains has features such as low-level reliability model, high security, public access, low-level privacy and transferable ownership when placed on a single database, properties are moderately trusted, low security, low public access, high privacy privacy and non-transferable. From the above structures, the blockchain is much more advanced than central storage.

 The following platforms are used to develop IoT systems using blockchain technology.

  1. IOTA: IOTA is a new blockchain and IoT platform called Next generation blockchains. This platform helps with high data integrity, high transaction performance and high blockchain performance through a few resources. It solves the limitations of blockchains [19].
  2. IOTIFY: Provides an online web solution solution to reduce blockchains technology limitations in the form of custom applications [20].
  3. Exec: An open source blockchain based tool. It helps your applications to the benefits of the cloud used [21].
  4. Xage: It is a secure IoT blockchain platform for adding automation and secure information [22].
  5. SONM: It is a medium-sized fog computing platform to provide secure cloud services.

IoTs and blockchains increase business opportunities and open up new markets where everyone or anything can communicate in real time with authenticity, privacy and security in the way they are used. The integration of these novel technologies will change the current world in which devices will communicate without people in various stages. The purpose of the framework is to obtain secure information in the right place, in the correct format, in real time. BC can be used to track billions of IoT connected objects, to link these objects, to enable transaction processing, to solve or eliminate failures and to create a flexible ecosystem to use the material in it. Hashing techniques used in data blocks by BC to create information privacy for users.

Nowadays, around the world smart devices are growing rapidly. They offer a lot of services to end users and attach to their daily lives. Mobiles currently use a mid-range mobile network for personal communication over the past decade. The smart phone is technically built to make the phone more usable for end users. We are now able to send text, photos, voice and video to each other using strong mobile networks. The smart phone can also connect to the internet easily by sending and receiving data within the mobile network. The Internet of Things describes a network of intelligent objects through which they can communicate and share information with each other using the Internet. Smart stuff with smart devices with built-in software, sensor and programs. Everything smart has a unique identifier on the network with their internal systems. Figure 1 shows that the smart device network network is a combination of intelligent device applications and an integrated framework installed by IEEE 802.15.4.

Reliability is a major problem in connected areas where many sensors, actuators, controllers and smart devices etc are connected. Smart devices are not just smart phones, it can be a smart refrigerator, Smart home entry, smart air conditioners, Smart hubs, Smart thermostat, Smart LED converter Colors, Smart Watches and smart tablets etc. . connected to each other via the internet. The proposed research program creates a study that increases communication reliability on smart devices using IEEE802.15.4. Transferring data from one configuration to another using wireless networks dates back to 1973 in the form of radio network packets. They were able to communicate with other similar configuration devices. Recent work is underway on a project called Serval Project. Provides networking location for Android communication devices on a sub-network. While our research is concerned about the reliable connection to the internet of smart devices. The main contribution of this study is the construction of a communication framework and provided reliable communication using IEEE802.15.4 between the internet of smart devices. Previous studies have focused on building and utilizing a communication framework, but such research does not create a complete framework for reliable communication between the internet of smart devices. Figure 2 represents an IoT node with a reliability feature.

 Integrity is a major problem in a variety of environments where many sensors, actuators, controllers and smart devices etc are connected to each other. The proposed study planned to build a study to increase communication reliability on devices using IEEE802.15.4. The main contribution of this study is the construction of a communication framework and provided reliable communication using IEEE802.15.4 between the internet of smart devices. Previous studies have focused on building and utilizing a communication framework, but such research does not create a complete framework for reliable communication between the internet of smart devices. The proposed online framework for smart devices based on IEEE 802.15.4 for reliable communication to improve the reliability of communication is tested and obtained positive results. The proposed study focuses on a framework for providing reliable internet connection to smart devices networks. Our main contribution to this study includes the reliability of the online communication framework for smart devices. This tutorial is very useful for the Internet of Things. The proposed framework was used for testing. Properly predicted in our full review. The overall effectiveness of the proposed device-based study device delays and communication reliability are assessed.

 4. OPPORTUNITIES

 The BC-IoT integration method has many amazing possibilities. It opens new doors for both of them together. Other opportunities are described as follows.

  1. Building Trust between Groups: The BC-IoT approach will build trust between various connected devices due to its security features. Only verified devices can connect to the network and all transaction blocks will first be verified by miners so they can enter BC.
  2. Reduce Costs: This method will reduce costs because it communicates directly without a third party. It removes all third-party nodes between sender and receiver. Provides direct communication.
  3. Reduce Time: This method greatly reduces time. Reduces transaction time taken from one day to two.
  4. Security & Privacy: Provides security and privacy to devices and information.
  5. Social Services: This approach provides social and social services to connected devices. All connected devices are able to communicate and share information between them.
  6. Financial Services: This method transfers funds securely without a third party. Provides fast, secure and independent financial services. Reduce costs and time.
  7. Risk management: This approach plays a key role in analysing and mitigating the risk of resource failure and transactions.

 5. CHALLENGES

 IoT and BC can face many challenges such as scale, store, skills, acquisition and the following are some of the challenges facing the integration approach.

  1. Diversity: BC can be suspended due to its heavy transaction load. Bitcoin storage exceeds 197 GB storage in 2019 [24]. Imagine if IoT meets BC the load will be much heavier than the current situation.
  2. Storage: The digital bag will be stored on all IoT nodes. At the same time, it will increase with its storage size which will be a challenging task and become a heavy load on each connected device.
  3. Lack of skills: BC new technology. It is known by very few people in the world. Therefore, it is also a challenge to train people professionally.
  4.  Discovery and Integration: In fact, BC was not built for IoT. It is a very challenging task for connected devices to find another device in BC and IoT. Therefore, IoT nodes can detect but can detect and integrate BC with another device.
  5. Privacy: The ledger is publicly distributed across all connected nodes. They see a ledger transaction. Therefore, privacy is a challenging task in an integrated approach.
  6. Collaboration: BC can be public or private. Therefore, the interaction between public and private blockchains is also a challenge in the BC-IoT approach.
  7. Rules and Regulations: IoT-BC will operate globally, and therefore deals with a number of rules and regulations for the use of this method worldwide.

6. CONCLUSION

BC and IoT are the novels tested in this document. Many opportunities and challenges are described. Also, the available platforms are listed in this article. This approach could be the future of the internet because it can transform the current internet system and transform it into a new one where all smart devices will connect to other devices using a peer-to-peer network in real time. It can reduce costs and current time and provide relevant information to the right device in real time. Therefore, it can be very helpful in the future.

References

 Tanweer Alam, Mohammed Aljohani (2016) Design a New Middleware for Communication in Ad Hoc Network of Android Smart Devices In: Second International Conference on Information and Communication Technology for Competitive Strategies ACM. 2015

Mohammed Aljohani, Tanweer Alam (2015) An algorithm for accessing traffic database using wireless technologies In: 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC).

Mohammed Aljohani, Tanweer Alam (2015) Design an M-learning framework for smart learning in ad hoc network of Android devices In: 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) IEEE.

Tanweer Alam, Mohammed Aljohani (2015) An approach to secure communication in mobile ad-hoc networks of Android devices In: International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) IEEE.

Tanweer Alam, Mohammed Aljohani (2015) Design and implementation of an Ad Hoc Network among Android smart devices In: International Conference on Green Computing and Internet of Things (ICGCIoT) IEEE.

Tanweer Alam (2021) Internet of Things and Blockchain-Based Framework for Coronavirus (COVID-19) Disease SSRN.

Tanweer Alam (2021) Blockchain-Enabled Mobile Healthcare System Architecture for the Real-Time Monitoring of the COVID-19 Patients SSRN. 2020

Tanweer Alam (2020) IoT-Fog-Blockchain Framework: Opportunities and Challenges International Journal of Fog Computing (IJFC) 3:

Tanweer Alam, Mohammed Aljohani (2020) Software Defined Networks: Review and Architecture IAIC Transactions on Sustainable Digital Innovation 1:

Tanweer Alam, Moath Erqsous (2020) The Real-Time Alert System for Prayers at Smart Masjid Scientific Journal of Informatics 7: 

Tanweer Alam (2020) Device-to-Device Communications in Cloud, MANET and Internet of Things Integrated Architecture Journal of Information Systems Engineering and Business Intelligence 6: 

Baha Rababah, Tanweer Alam, Rasit Eskicioglu (2020) The Next Generation Internet of Things Architecture Towards Distributed Intelligence: Reviews, Applications, and Research Challenges Journal of Telecommunication, Electronic and Computer Engineering 12: 

Tanweer Alam, Abdulrahman A Salem, Ahmad O Alsharif, Abdulaziz M Alhejaili (2020) Smart Home Automation Towards the Development of Smart Cities APTIKOM Journal on Computer Science and Information Technologies 5:    13-20.

Tanweer Alam, Baha Rababah, Arshad Ali, Shamimul Qamar (2020) Distributed Intelligence at the Edge on IoT Networks Annals of Emerging Technologies in Computing (AETiC) 4: 

Tanweer Alam, Abdirahman Ahmed Hadi, Rayyan Qari Shahabuddin Najam, Shamimul Qamar (2020) Design a Mobile Application for Children’s Tracking in Crowded Environments TEST Engineering and Management 83: .

Tanweer Alam (2020) Performance evaluation of blockchains in the internet of things Computer Science and Information Technologies 1:

Tanweer Alam (2020) CMI Computing: A Cloud, MANET and Internet of Things Integration for Future Internet JAMBURA JOURNAL OF INFORMATICS 2:

Tanweer Alam, Mohammed Aljohani (2020) M-Learning: Positioning the Academics to the Smart devices in the Connected Future JOIV: International Journal on Informatics Visualization 4:

Tanweer Alam, Shamimul Qamar (2020) Coronavirus Disease (COVID-19): Reviews, Applications, and Current Status Jurnal Informatika Universitas Pamulang 5:

Tanweer Alam Yazeed Mohammed Alharbi Firas Adel Abusallama Ahmad Osama Hakeem (2020) Smart Campus Mobile Application Toward the Development of Smart Cities International Journal of Applied Sciences and Smart Technologies 12:

Tanweer Alam (2020) Internet of Things: A Secure Cloud-based MANET Mobility Model International Journal of Network Security 22:

Tanweer Alam (2020) Design a blockchain-based middleware layer in the Internet of Things Architecture JOIV: International Journal on Informatics Visualization 4:

Tanweer Alam (2020) mHealth Communication Framework using Blockchain and IoT Technologies International Journal of Scientific & Technology Research 9:

Tanweer Alam, Mohammed Aljohani (2020) Decision Support System for Real-Time People Counting in a Crowded Environment International Journal of Electronics and Information Engineering 12:

Tanweer Alam (2020) Cloud Computing and Its Role in the Information Technology IAIC Transactions on Sustainable Digital Innovation 1:

Tanweer Alam (2020) Efficient and Secure Data Transmission Approach in Cloud-MANET-IoT Integrated Framework Journal of Telecommunication, Electronic and Computer Engineering 12:

Tanweer Alam (2020) Tactile Internet and Its Contribution in the Development of Smart Cities International Journal of Electronics and Information Engineering 12:

Tanweer Alam (2020) Cloud-MANET and its Role in Software-Defined Networking Transactions on Science and Technology 7:   1-7.

Tanweer Alam (2020) Middleware Implementation in MANET of Android Devices International Journal of Electronics and Information Engineering. 12:

Tanweer Alam, Shamimul Qamar, Amit Dixit, Mohamed Benaida (2020) Genetic Algorithm: Reviews, Implementations, and Applications International Journal of Engineering Pedagogy (iJEP) 10:   57-77 December. 2019

Tanweer Alam, Baha Rababah (2019) Convergence of MANET in Communication among Smart Devices in IoT International Journal of Wireless and Microwave Technologies (IJWMT) 9:

Tanweer Alam (2019) 5G-Enabled Tactile Internet for Smart Cities: Vision, Recent Developments, and Challenges JURNAL INFORMATIKA 13:   1-10.

Tanweer Alam (2019) A Middleware Framework between Mobility and IoT Using IEEE 802.15.4e Sensor Networks Jurnal Online Informatika 4:

Tanweer Alam (2019) Blockchain and its Role in the Internet of Things (IoT) nternational Journal of Scientific Research in Computer Science, Engineering and Information Technology 5:

Tanweer Alam (2019) IoT-Fog: A Communication Framework using Blockchain in the Internet of Things International Journal of Recent Technology and Engineering 7:  2018

Tanweer Alam (2018) A Reliable Framework for Communication in Internet of Smart Devices using IEEE 802.15.4 ARPN Journal of Engineering and Applied Sciences 13:

Tanweer Alam (2018) A Reliable Communication Framework and its Use in Internet of Things (IoT) International Journal of Scientific Research in Computer Science, Engineering and Information Technology 3:

Tanweer Alam, Mohamed Benaida (2018) The Role of Cloud-MANET Framework in the Internet of Things (IoT) International Journal of Online and Biomedical Engineering 14:

Tanweer Alam, Mohamed Benaida (2018) CICS: Cloud–Internet Communication Security Framework for the Internet of Smart Devices International Journal of Interactive Mobile Technologies (iJIM) 12:   74-84. 2017

Tanweer Alam (2017) Middleware Implementation in Cloud-MANET Mobility Model for Internet of Smart Devices International Journal of Computer Science and Information Security 17:   86-94.

Tanweer Alam (2017) Fuzzy Control Based Mobility Framework for Evaluating Mobility Models in MANET of Smart Devices ARPN Journal of Engineering and Applied Sciences 12:

Alam, Tanweer, and Mohamed Benaida. "Blockchain, Fog and IoT Integrated Framework: Review, Architecture and Evaluation.", Technology Reports of Kansai University 62, no. 2 (2020).

Sharma, Abhilash, Tanweer Alam, and Dimpi Srivastava. "Ad hoc network architecture based on mobile Ipv6 development." Advances in Computer Vision and Information Technology 224 (2008).

Alam, Tanweer. "Blockchain-based Big Data Analytics Approach for Smart Cities." Authorea Preprints (2020).

Alam, Tanweer, and B. K. Sharma. "A new optimistic mobility model for mobile ad hoc Networks." International Journal of Computer Applications 8, no. 3 (2010): 1-4.

Alam, Tanweer, Parveen Kumar, and Prabhakar Singh. "Searching mobile nodes using modified column mobility model." International Journal of Computer Science and Mobile Computing 3, no. 1 (2014): 513-518.

Alam, Tanweer, and Mohamed Benaida. "Blockchain and Internet of Things in Higher Education", Universal Journal of Educational Research 8(5): 2164-2174, 2020. DOI: 10.13189/ujer.2020.080556

Alam, Tanweer, and Moath Erqsous. "The Real-Time Alert System for Prayers at Smart Masjid." Scientific Journal of Informatics 7, no. 2 (2020): 166-172.

Singh, Parbhakar, Parveen Kumar, and Tanweer Alam. "Generating different mobility scenarios in ad hoc networks." International Journal of Electronics Communication and Computer Technology 4, no. 2 (2014): 582-591.

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By Sachin Kotasthane

In his book, 21 Lessons for the 21st Century, the historian Yuval Noah Harari highlights the complex challenges mankind will face on account of technological challenges intertwined with issues such as nationalism, religion, culture, and calamities. In the current industrial world hit by a worldwide pandemic, we see this complexity translate in technology, systems, organizations, and at the workplace.

While in my previous article, Humane IIoT, I discussed the people-centric strategies that enterprises need to adopt while onboarding IoT initiatives of industrial IoT in the workforce, in this article, I will share thoughts on how new-age technologies such as AI, ML, and big data, and of course, industrial IoT, can be used for effective management of complex workforce problems in a factory, thereby changing the way people work and interact, especially in this COVID-stricken world.

Workforce related problems in production can be categorized into:

  1. Time complexity
  2. Effort complexity
  3. Behavioral complexity

Problems categorized in either of the above have a significant impact on the workforce, resulting in a detrimental effect on the outcome—of the product or the organization. The complexity of these problems can be attributed to the fact that the workforce solutions to such issues cannot be found using just engineering or technology fixes as there is no single root-cause, rather, a combination of factors and scenarios. Let us, therefore, explore a few and seek probable workforce solutions.8829066088?profile=RESIZE_584x

Figure 1: Workforce Challenges and Proposed Strategies in Production

  1. Addressing Time Complexity

    Any workforce-related issue that has a detrimental effect on the operational time, due to contributing factors from different factory systems and processes, can be classified as a time complex problem.

    Though classical paper-based schedules, lists, and punch sheets have largely been replaced with IT-systems such as MES, APS, and SRM, the increasing demands for flexibility in manufacturing operations and trends such as batch-size-one, warrant the need for new methodologies to solve these complex problems.

    • Worker attendance

      Anyone who has experienced, at close quarters, a typical day in the life of a factory supervisor, will be conversant with the anxiety that comes just before the start of a production shift. Not knowing who will report absent, until just before the shift starts, is one complex issue every line manager would want to get addressed. While planned absenteeism can be handled to some degree, it is the last-minute sick or emergency-pager text messages, or the transport delays, that make the planning of daily production complex.

      What if there were a solution to get the count that is almost close to the confirmed hands for the shift, an hour or half, at the least, in advance? It turns out that organizations are experimenting with a combination of GPS, RFID, and employee tracking that interacts with resource planning systems, trying to automate the shift planning activity.

      While some legal and privacy issues still need to be addressed, it would not be long before we see people being assigned to workplaces, even before they enter the factory floor.

      During this course of time, while making sure every line manager has accurate information about the confirmed hands for the shift, it is also equally important that health and well-being of employees is monitored during this pandemic time. Use of technologies such as radar, millimeter wave sensors, etc., would ensure the live tracking of workers around the shop-floor and make sure that social distancing norms are well-observed.

    • Resource mapping

      While resource skill-mapping and certification are mostly HR function prerogatives, not having the right resource at the workstation during exigencies such as absenteeism or extra workload is a complex problem. Precious time is lost in locating such resources, or worst still, millions spent in overtime.

      What if there were a tool that analyzed the current workload for a resource with the identified skillset code(s) and gave an accurate estimate of the resource’s availability? This could further be used by shop managers to plan manpower for a shift, keeping them as lean as possible.

      Today, IT teams of OEMs are seen working with software vendors to build such analytical tools that consume data from disparate systems—such as production work orders from MES and swiping details from time systems—to create real-time job profiles. These results are fed to the HR systems to give managers the insights needed to make resource decisions within minutes.

  2. Addressing Effort Complexity

    Just as time complexities result in increased  production time, problems in this category result in an increase in effort by the workforce to complete the same quantity of work. As the effort required is proportionate to the fatigue and long-term well-being of the workforce, seeking workforce solutions to reduce effort would be appreciated. Complexity arises when organizations try to create a method out-of-madness from a variety of factors such as changing workforce profiles, production sequences, logistical and process constraints, and demand fluctuations.

    Thankfully, solutions for this category of problems can be found in new technologies that augment existing systems to get insights and predictions, the results of which can reduce the efforts, thereby channelizing it more productively. Add to this, the demand fluctuations in the current pandemic, having a real-time operational visibility, coupled with advanced analytics, will ensure meeting shift production targets.

    • Intelligent exoskeletons

      Exoskeletons, as we know, are powered bodysuits designed to safeguard and support the user in performing tasks, while increasing overall human efficiency to do the respective tasks. These are deployed in strain-inducing postures or to lift objects that would otherwise be tiring after a few repetitions. Exoskeletons are the new-age answer to reducing user fatigue in areas requiring human skill and dexterity, which otherwise would require a complex robot and cost a bomb.

      However, the complexity that mars exoskeleton users is making the same suit adaptable for a variety of postures, user body types, and jobs at the same workstation. It would help if the exoskeleton could sense the user, set the posture, and adapt itself to the next operation automatically.

      Taking a leaf out of Marvel’s Iron Man, who uses a suit that complements his posture that is controlled by JARVIS, manufacturers can now hope to create intelligent exoskeletons that are always connected to factory systems and user profiles. These suits will adapt and respond to assistive needs, without the need for any intervention, thereby freeing its user to work and focus completely on the main job at hand.

      Given the ongoing COVID situation, it would make the life of workers and the management safe if these suits are equipped with sensors and technologies such as radar/millimeter wave to help observe social distancing, body-temperature measuring, etc.

    • Highlighting likely deviations

      The world over, quality teams on factory floors work with checklists that the quality inspector verifies for every product that comes at the inspection station. While this repetitive task is best suited for robots, when humans execute such repetitive tasks, especially those that involve using visual, audio, touch, and olfactory senses, mistakes and misses are bound to occur. This results in costly reworks and recalls.

      Manufacturers have tried to address this complexity by carrying out rotation of manpower. But this, too, has met with limited success, given the available manpower and ever-increasing workloads.

      Fortunately, predictive quality integrated with feed-forwards techniques and some smart tracking with visuals can be used to highlight the area or zone on the product that is prone to quality slips based on data captured from previous operations. The inspector can then be guided to pay more attention to these areas in the checklist.

  3. Addressing Behavioral Complexity

    Problems of this category usually manifest as a quality issue, but the root cause can often be traced to the workforce behavior or profile. Traditionally, organizations have addressed such problems through experienced supervisors, who as people managers were expected to read these signs, anticipate and align the manpower.

    However, with constantly changing manpower and product variants, these are now complex new-age problems requiring new-age solutions.

    • Heat-mapping workload

      Time and motion studies at the workplace map the user movements around the machine with the time each activity takes for completion, matching the available cycle-time, either by work distribution or by increasing the manpower at that station. Time-consuming and cumbersome as it is, the complexity increases when workload balancing is to be done for teams working on a single product at the workstation. Movements of multiple resources during different sequences are difficult to track, and the different users cannot be expected to follow the same footsteps every time.

      Solving this issue needs a solution that will monitor human motion unobtrusively, link those to the product work content at the workstation, generate recommendations to balance the workload and even out the ‘congestion.’ New industrial applications such as short-range radar and visual feeds can be used to create heat maps of the workforce as they work on the product. This can be superimposed on the digital twin of the process to identify the zone where there is ‘congestion.’ This can be fed to the line-planning function to implement corrective measures such as work distribution or partial outsourcing of the operation.

    • Aging workforce (loss of tribal knowledge)

      With new technology coming to the shop-floor, skills of the current workforce get outdated quickly. Also, with any new hire comes the critical task of training and knowledge sharing from experienced hands. As organizations already face a shortage of manpower, releasing more hands to impart training to a larger workforce audience, possibly at different locations, becomes an even more daunting task.

      Fully realizing the difficulties and reluctance to document, organizations are increasingly adopting AR-based workforce trainings that map to relevant learning and memory needs. These AR solutions capture the minutest of the actions executed by the expert on the shop-floor and can be played back by the novice in-situ as a step-by-step guide. Such tools simplify the knowledge transfer process and also increase worker productivity while reducing costs.

      Further, in extraordinary situations such  as the one we face at present, technologies such as AR offer solutions for effective and personalized support to field personnel, without the need to fly in specialists at multiple sites. This helps keep them safe, and accessible, still.

Key takeaways and Actionable Insights

The shape of the future workforce will be the result of complex, changing, and competing forces. Technology, globalization, demographics, social values, and the changing personal expectations of the workforce will continue to transform and disrupt the way businesses operate, increasing the complexity and radically changing where, and when of future workforce, and how work is done. While the need to constantly reskill and upskill the workforce will be humongous, using new-age techniques and technologies to enhance the effectiveness and efficiency of the existing workforce will come to the spotlight.

8829067296?profile=RESIZE_710x

Figure 2: The Future IIoT Workforce

Organizations will increasingly be required to:

  1. Deploy data farming to dive deep and extract vast amounts of information and process insights embedded in production systems. Tapping into large reservoirs of ‘tribal knowledge’ and digitizing it for ingestion to data lakes is another task that organizations will have to consider.
  2. Augment existing operations systems such as SCADA, DCS, MES, CMMS with new technology digital platforms, AI, AR/VR, big data, and machine learning to underpin and grow the world of work. While there will be no dearth of resources in one or more of the new technologies, organizations will need to ‘acqui-hire’ talent and intellectual property using a specialist, to integrate with existing systems and gain meaningful actionable insights.
  3. Address privacy and data security concerns of the workforce, through the smart use of technologies such as radar and video feeds.

Nonetheless, digital enablement will need to be optimally used to tackle the new normal that the COVID pandemic has set forth in manufacturing—fluctuating demands, modular and flexible assembly lines, reduced workforce, etc.

Originally posted here.

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Provisioning, managing and securing devices in an IoT product requires careful planning at the very start of the process. Rigorous evaluation of options, then a Proof of Concept helps determine the right solution. Once the POC has been approved, the IoT product moves to production. Then the real fun starts and many strategic considerations come into play. We can list them as follows:

  • Robust and secure OTA software updates

  • Security by design

  • Scalability

  • Automation

  • Remote terminal management

  • Device configuration, monitoring & troubleshooting

Robust and secure OTA software updates

Robust and secure OTA software updates are essential for keeping IoT devices secure as the software on these devices will become outdated during their lifetime and vulnerabilities are certain to arise if left in their initial states. Therefore a secure, risk-tolerant, and efficient update mechanism must be at the core of each product development team from the inception of the project to the end of its life.

How about a homegrown solution?

Homegrown solutions are less likely to be best-of-breed, can be hard to scale, can suffer from over customisation and scope creep, come at an inherently high cost and can be left in trouble if the star developers behind their creation suddenly jump ship and leave the organisation.  They also often lack the requirements needed to ensure security and robustness of software updates. Various open source solutions exist, but none provide an end-to-end solution and lack the overall functionality to make them enterprise-grade. Generic public cloud IoT stacks wish to cater to the entire IoT value chain but fail to deliver a purpose-built solution for software updates. Proprietary and platform solutions cause lock-in to specific cloud infrastructure, operating system, or development tools.

The common thread among all of these solutions is the lack of a fully optimized end-to-end OTA software update and device management infrastructure that can minimize risk, increase efficiency and enhance security and uptime.

Security by design

A device security breach incident can interrupt operations, damage systems, and negatively impact both virtual and physical processes. This translates into unhappy customers and lost business. As Colin Duggan, the Founder and CEO at BG Networks says in an interview with the Device Chronicle, “It is difficult to add security after the design has been completed. There are a number of reasons for this. Embedded systems have limited MHz, memory, and limitations of network interfaces on embedded processors. Security features can be added after the fact but usually will not close off all the vulnerabilities.” That is why it is so important to ensure security by design, in the very early stages of the product’s lifecycle.

IoT product security should be approached holistically with a framework that addresses the people, devices and process. To help IoT professionals make the right decisions concerning their product development, we designed a simple framework based on these factors and called it the Triangle of Trust:
Triangle_of_Trust-1024x575.png

Scalability

There’s a significant difference between managing a small number of embedded devices and having thousands or even millions of devices deployed in the field. Microsoft’s new IoT Signals report found lack of scalability as a leading cause for IoT project failures. Complexity is one of the greatest scalability issues. As such, choosing the right solution with the right architecture is important to safeguard the long-term management viability of your fleet of connected devices. More on the topic of IoT scalability can be read here.

Automation

When one of the arms of the Triangle of Trust fails, the other two are endangered. To prevent any risks arising from human mistakes, automating some of the processes is a solution that might save your business thousands of dollars. Mender.io is an OTA software update manager for Linux-based embedded devices, and it also offers a wide range of automations to securely manage these devices. One of the features that Mender offers is automatic retry of failed device deployments. Deployments to devices might fail for various intermittent reasons like loss of power, network or device usage. Automatic retry upon failures reduces device deployment error rates up to 90%. This translates to time and money savings managing deployments, and also leads to customers receiving the updates faster.

Remote Management

Remote management is a necessity for any kind of embedded device. Any company rolling out its IoT products needs to have control of its systems from a central location. SSH, secure tunneling and remote terminal access is preferred by service providers to VPN access as they can assure their customers of security when accessing and troubleshooting devices. Furthermore, the management involves grouping and accessing embedded devices, provisioning, configuring, and monitoring remotely and securely.

Seeing the necessity for not only secure over-the-air processes, but also for reliable ways of monitoring, provisioning, configuring, grouping, and accessing the embedded devices, the team behind Mender decided to expand their offering by the mentioned remote management features. Mender is open source software meaning there are many contributors to make it better and support a variety of customer hardware and software such as NVIDIA Jetson and NXP's family of iMX processors. It provides flexibility in choosing your infrastructure, software, and hardware from prototyping to production which means there is no vendor lock-in. Mender supports all device software updates from a full disk image to application updates with the freedom to customize the update and installation process to fit your workflow. It is also integrated with Google Cloud and Microsoft Azure IoT for easy device authentication. 

Device configuration, troubleshooting and monitoring

A proper device management set up should never be overlooked. Robust and secure device management is a necessary cornerstone for an IoT product and therefore you need to find a high quality solution. Once you deploy thousands or millions of devices into the field you’ll need to be able to configure them properly, gather the data, and quickly troubleshoot any arising problems. Many organisations treat these capabilities as an afterthought. Engineers realize that they need some kind of device management solution right before their deadlines and product releases, which results in rushed fixes being made, that may have serious implications for the robustness and security of connected devices.

Conclusion

In order to roll out a successful, secure, and robust IoT product a few things have to be taken into consideration before the release. To ensure security by design from the earliest stages of the product life cycle, the team behind the IoT product needs to find a solution for deploying secure and robust OTA updates, remotely monitor, configure, and troubleshoot the devices, and automate necessary processes in order to avoid human-made mistakes.

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In this blog, we’ll discuss how users of Edge Impulse and Nordic can actuate and stream classification results over BLE using Nordic’s UART Service (NUS). This makes it easy to integrate embedded machine learning into your next generation IoT applications. Seamless integration with nRF Cloud is also possible since nRF Cloud has native support for a BLE terminal. 

We’ve extended the Edge Impulse example functionality already available for the nRF52840 DK and nRF5340 DK by adding the abilities to actuate and stream classification outputs. The extended example is available for download on github, and offers a uniform experience on both hardware platforms. 

Using nRF Toolbox 

After following the instructions in the example’s readme, download the nRF Toolbox mobile application (available on both iOS and Android) and connect to the nRF52840 DK or the nRF5340 DK that will be discovered as “Edge Impulse”. Once connected, set up the interface as follows so that you can get information about the device, available sensors, and start/stop the inferencing process. Save the preset configuration so that you can load it again for future use. Fill out the text of the various commands to use the same convention as what is used for the Edge Impulse AT command set. For example, sending AT+RUNIMPULSE starts the inferencing process on the device. 

IMG_7478_474aa59323.jpg
Figure 1. Setting up the Edge Impulse AT Command set

Once the appropriate AT command set mapping to an icon has been done, hit the appropriate icon. Hitting the ‘play’ button cause the device to start acquiring data and perform inference every couple of seconds. The results can be viewed in the “Logs” menu as shown below.

NUS_ble_logger_view_e9daba3698.jpg
Figure 2. Classification Output over BLE in the Logs View

Using nRF Cloud

Using the nRF Connect for Cloud mobile app for iOS and Android, you can turn your smartphone into a BLE gateway. This allows users to easily connect their BLE NUS devices running Edge Impulse to the nRF Cloud as an easy way to send the inferencing conclusions to the cloud. It’s as easy as setting up the BLE gateway through the app, connecting to the “Edge Impulse” device and watching the same results being displayed in the “Terminal over BLE” window shown below!

Screen_Hunter_229_Feb_16_23_45_26c8913865.jpgFigure 3. Classification Output Shown in nRF Cloud

Summary

Edge Impulse is supercharging IoT with embedded machine learning and we’ve discussed a couple of ways you can easily send conclusions to either the smartphone or to the cloud by leveraging the Nordic UART Service. We look forward to seeing how you’ll leverage Edge Impulse, Nordic and BLE to create your next gen IoT application.  

 

Article originally written for the Edge Impulse blog by Zin Thein Kyaw, Senior User Success Engineer at Edge Impulse.

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The Internet of Things is growing at breakneck speed. One report suggests that the global market for IoT will surpass $1.38 trillion by 2026 — a substantial increase from its 2020 valuation of $761.4 billion.

The IoT is nothing without IoT platforms — middleware that connects sensors, assets, data, software, and business processes. It brings all the different components of your IoT infrastructure together so your business can get every possible benefit.

There are many IoT platforms on the market, and it’s important to find the right one for your business. This can be a challenging task, with lots of complex and competing information to sift through. 

In this article, we’ve put together a list of the main factors that should drive your decision when settling on an IoT platformhelping you make an informed decision that leads to the best solution for your needs.

Why you need an IoT platform?

There are many reasons to consider investing in an IoT platform. Essentially, the job of an IoT platform is to act as a ready-made framework for all your IoT infrastructure, pulling everything together and helping you start getting the benefits as quickly as possible. Here are some of the biggest advantages of a good IoT platform:

  • It saves money, by making it more likely that your project will succeed and reducing the amount of time you’ll need to spend developing your own systems and fixing problems. Without relying on an IoT platform, it’s more likely that your project will fail and cost money. IoT platforms also centralize the management of your IoT network which is much more cost-efficient than trying to manage a scattered collection of devices.
  • It helps provide security, ensuring your devices are safe, keeping your valuable data safe from the hands of hackers and cybercriminals, and giving you peace of mind.
  • It helps you go to market quicker. IoT platforms take care of many aspects of your IoT project, saving you significant time and allowing you to roll out a prototype quickly.
  • Good IoT platforms come packed with ready-made features, from help with billing to data analytics support, all geared towards helping you get the most out of your IoT infrastructure and providing valuable support to every member of your team.
  • Device and data integration. IoT platforms bring all your devices together and integrate them into one central system. This way, you can integrate the data with your enterprise systems and enhance your organization’s existing processes. The result is a more cohesive network with each part supporting the whole, as opposed to a disparate collection of individual devices.
  • It helps improve and streamline operations across your entire business by bringing IoT data together with data from external sources, allowing for a more holistic view of your entire organization which can drive better working processes and help you hit your goals in various areas.

What to look for in an IoT platform?

The best IoT platforms can provide a whole host of major advantages to your project and business as a whole. By providing connectivity as a service, they simplify the process of managing IoT devices with various connectivity technologies and remove the need to establish a contract with multiple network providers. 

But it’s important to pick the right platform for your specific needs. Here are some things to consider to ensure you make the right choice.

Connectivity management

Connectivity is a huge factor when it comes to IoT. Each project and organization has its own specific connectivity requirements, and this will have a direct impact on which IoT platform is the best fit.

Some IoT platforms are more specialized in certain technologies than others. Ideally, you should choose a platform that’s able to orchestrate a range of different connectivity technologies like LoRaWAN, Sigfox, NB-IoT, LTE Cat. M1, 4G, 5G, and WIFI.

Geographical location is also something to consider. Your IoT platform should be able to support IoT applications and devices in all the different geographical regions you need it to.

Scalability

Your IoT project will almost certainly grow over time. As this technology expands and becomes more widely used, almost every business is likely to find itself using more and more IoT devices and functions across multiple use cases.

Your IoT platform should be prepared for this. Select a platform that can comfortably scale as the project grows and is fit for all IoT project states from just a handful of devices in one area to thousands spread across many regions.

The best IoT platforms should be able to scale across a range of different deployment models, such as:

  • In a public cloud
  • In a private cloud
  • On your business premises

Security

Another major concern for IoT networks is security. Attacks on IoT devices are on the rise, with 33% of infected devices now part of the IoT. It’s essential to make sure you choose an IoT platform that prioritizes security.

If you don’t take security seriously, you’re putting your IoT infrastructure at risk of cyberattacks, which could result in downtime, the loss of sensitive data, and serious reputational damage. On top of this, many companies have to comply with strict requirements when it comes to data ownership and security, which means you could face legal penalties if your data is breached.

It’s no longer enough to simply secure your business premises — in our increasingly remotely connected world, you have to keep your devices safe wherever they are. Your IoT platform should also be able to integrate with common cloud infrastructures like Google Cloud, Microsoft Azure, and Amazon AWS.

Usability

The whole point of IoT is to make your life and business processes easier. It shouldn’t add an extra layer of difficulty and complexity to your systems. The best IoT platforms are straightforward and easy to integrate with existing processes.

The main user groups to consider here are:

  • The people who will actually be using the system — your end-users
  • The people whose job it is to maintain the system like your company’s internal engineers

For both of these groups, the IoT platform should be as user-friendly as possible with minimal friction and challenges. This not only helps you get the most out of your technology but also keeps your team happy and stress-free.

End-user application

It is crucial to make sure that your IoT platform can be integrated with your final application. Typically, you want the platform to have a standardized interface (REST API) that allows you to connect your end-user smart application and make use of the data for your particular business case.

Your chosen platform should also support the visualization of data during a pilot, as this helps you understand your IoT systems as closely as possible and communicate this to other members of your organization.

Resilience to technological change

If there’s one thing we can be sure of when it comes to technology, it’s that constant change is unavoidable. This is a good thing for businesses and ensures constant progress and development, but when it comes to IoT systems it’s essential to prepare for this ongoing change.

Your hardware, connectivity, and applications need to be adaptable and resistant to change. Otherwise, you’ll run into issues like technological lock-in where you’re forced to use technology that is no longer sufficient for the demands of the time.

One way to ensure resistance to change is to make it possible to exchange the components of your IoT solution at any time, without negatively impacting the overall final application. This allows you to modify and upgrade your infrastructure bit-by-bit over time without major delays and downtime.

When it comes to IoT platforms, there is no one-size-fits-all answer. You need to take the time to figure out which platforms are the best fit for your unique set of needs and challenges, and pick one that can help you get the most out of your network.

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From a salt shaker with a built-in speaker to smart water devices that bring clean water to communities with weak infrastructure, connected devices are increasingly advancing into all areas of our lives. But more connectivity brings more possibilities for crippling issues that can impact product development, operations, and maintenance. IoT developers must consider how to plan for firmware architecture that leads to a better, stickier product.

Competition among connected device manufacturers is swelling in every corner of the industry, and user patience for clunky products won’t get the benefit of the doubt that developers might otherwise have had in the IoT’s nascent days. As users become more dependent on connected devices, consumer demands that those devices consistently function well - and securely - become the expectation. There remains, of course, work to be done: a quick Google search reveals stories like the Fitbit firmware update that destroyed the device battery, or the Tesla key fobs that could be overwritten and hijacked until a patch was rolled out.    

These stories underscore that the IoT ecosystem’s connected nature requires that hardware developers approach product development differently - and take firmware updates seriously. It used to be that developers could write static firmware for specific device use cases or commoditized products and, once released, have no further interaction or engagement with the product. That system no longer works. To have a successful product, IoT device manufacturers need to invest in design and in firmware development equally.

Whether it’s BLE on phones or LTE or Zigby and other mesh networks, IoT devices are connected, regularly transmitting sensitive and personal data to and from the cloud. The near limitless reach of modern connected devices across all areas of our lives, paired with the high price point of most IoT devices underscores that IoT developers must have a plan (and not an after-the-fact reaction) for firmware maintenance. Putting that plan in motion requires three considerations:

Device monitoring

Ubiquitous connectivity brings with it major challenges, but it also brings opportunities. Among other things, it allows automated device health monitoring. The typical process of releasing a product relies on users’ reporting a problem and requiring them to physically return the device to be evaluated, repaired, and returned. Simply put, this is a huge waste of money and time, and it also risks frustrating the customer to the point of losing them entirely. Using customers as your testers is simply a terrible business decision. (Maybe you could get away with it if you were the only game in town, but IoT device makers don’t have that luxury anymore). Automated device monitoring is the solution. By regularly analyzing the health of devices and flagging potential problems immediately, a monitoring system can help device makers catch and fix issues in hours that would have otherwise taken them weeks to root cause. Designing embedded systems with such capabilities gives critical observability into performance, stability, and overall health - either of a single device or of a fleet of millions. 

Repair

Shipping products that require an update or patch is inevitable for even the most talented and thorough teams. Just ask NASA. While no one can avoid updates entirely, it is possible to detect fleet-wide issues and solve them without burdening users. The key is to roll out updates incrementally, starting with a small number of devices and ramping up over time. This limits the impact of any new issues and insulates most of your users from the churn of getting a few bugfix releases in a row.  Another good option is to implement an A/B update system if you have enough flash memory. This allows your device to download an update in the background with no user impact and simply prompts the user to reboot once the update is ready. Fast and simple update flows like A/B updates are key to compliance, and prevent too much fragmentation across your fleet. Last but not least, it is important to pair regular updates with a monitoring system so you can quickly identify problems with the update, and rollouts can be paused or aborted altogether.

Building with security in mind

The ubiquity of IoT devices has accelerated customer demands for robust device security in lockstep, with regulatory bodies becoming more serious (and punitive) about security requirements and standards. For those building smart devices, I would offer these principles as table stakes for security: 

  1. Devices must be updateable. 
  2. Trusted boot is no longer optional. You need a chain of trust to control the firmware running on your device.
  3. Rotate secrets and don’t use a master secret. Whether that means a set of encryption keys or other secrets to make devices functional, they must be dynamically changed, so the compromise of one device does not lead to the compromise of others. 

Software teams have long embraced iterative processes, and IoT device developers can learn much from this process. Focusing on firmware architecture that is responsive, observable, and proactive, lets device manufacturers ship a better product and create a happier customer base.

François Baldassari is the Founder and CEO of Memfault, a cloud-based observability platfrom for hardware devices. Prior to Memfault, François worked on developer infrastructure initiatives at Pebble and Oculus.

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IoT in Mining

Flowchart of IoT in Mining

by Vaishali Ramesh

Introduction – Internet of Things in Mining

The Internet of things (IoT) is the extension of Internet connectivity into physical devices and everyday objects. Embedded with electronics, Internet connectivity, and other forms of hardware; these devices can communicate and interact with others over the Internet, and they can be remotely monitored and controlled. In the mining industry, IoT is used as a means of achieving cost and productivity optimization, improving safety measures and developing their artificial intelligence needs.

IoT in the Mining Industry

Considering the numerous incentives it brings, many large mining companies are planning and evaluating ways to start their digital journey and digitalization in mining industry to manage day-to-day mining operations. For instance:

  • Cost optimization & improved productivity through the implementation of sensors on mining equipment and systems that monitor the equipment and its performance. Mining companies are using these large chunks of data – 'big data' to discover more cost-efficient ways of running operations and also reduce overall operational downtime.
  • Ensure the safety of people and equipment by monitoring ventilation and toxicity levels inside underground mines with the help of IoT on a real-time basis. It enables faster and more efficient evacuations or safety drills.
  • Moving from preventive to predictive maintenance
  • Improved and fast-decision making The mining industry faces emergencies almost every hour with a high degree of unpredictability. IoT helps in balancing situations and in making the right decisions in situations where several aspects will be active at the same time to shift everyday operations to algorithms.

IoT & Artificial Intelligence (AI) application in Mining industry

Another benefit of IoT in the mining industry is its role as the underlying system facilitating the use of Artificial Intelligence (AI). From exploration to processing and transportation, AI enhances the power of IoT solutions as a means of streamlining operations, reducing costs, and improving safety within the mining industry.

Using vast amounts of data inputs, such as drilling reports and geological surveys, AI and machine learning can make predictions and provide recommendations on exploration, resulting in a more efficient process with higher-yield results.

AI-powered predictive models also enable mining companies to improve their metals processing methods through more accurate and less environmentally damaging techniques. AI can be used for the automation of trucks and drills, which offers significant cost and safety benefits.

Challenges for IoT in Mining 

Although there are benefits of IoT in the mining industry, implementation of IoT in mining operations has faced many challenges in the past.

  • Limited or unreliable connectivity especially in underground mine sites
  • Remote locations may struggle to pick up 3G/4G signals
  • Declining ore grade has increased the requirements to dig deeper in many mines, which may increase hindrances in the rollout of IoT systems

Mining companies have overcome the challenge of connectivity by implementing more reliable connectivity methods and data-processing strategies to collect, transfer and present mission critical data for analysis. Satellite communications can play a critical role in transferring data back to control centers to provide a complete picture of mission critical metrics. Mining companies worked with trusted IoT satellite connectivity specialists such as ‘Inmarsat’ and their partner eco-systems to ensure they extracted and analyzed their data effectively.

 

Cybersecurity will be another major challenge for IoT-powered mines over the coming years

 As mining operations become more connected, they will also become more vulnerable to hacking, which will require additional investment into security systems.

 

Following a data breach at Goldcorp in 2016, that disproved the previous industry mentality that miners are not typically targets, 10 mining companies established the Mining and Metals Information Sharing and Analysis Centre (MM-ISAC) to share cyber threats among peers in April 2017.

In March 2019, one of the largest aluminum producers in the world, Norsk Hydro, suffered an extensive cyber-attack, which led to the company isolating all plants and operations as well as switching to manual operations and procedures. Several of its plants suffered temporary production stoppages as a result. Mining companies have realized the importance of digital security and are investing in new security technologies.

Digitalization of Mining Industry - Road Ahead

Many mining companies have realized the benefits of digitalization in their mines and have taken steps to implement them. There are four themes that are expected to be central to the digitalization of the mining industry over the next decade are listed below:

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The above graph demonstrates the complexity of each digital technology and its implementation period for the widespread adoption of that technology. There are various factors, such as the complexity and scalability of the technologies involved in the adoption rate for specific technologies and for the overall digital transformation of the mining industry.

The world can expect to witness prominent developments from the mining industry to make it more sustainable. There are some unfavorable impacts of mining on communities, ecosystems, and other surroundings as well. With the intention to minimize them, the power of data is being harnessed through different IoT statements. Overall, IoT helps the mining industry shift towards resource extraction, keeping in mind a particular time frame and footprint that is essential.

Originally posted here.

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How IoT Tools Are Mining Manufacturing's Gold

IIoT will allow assets to perform more cost-effectively – so the better the data, the greater the savings.

Ricardo Buranello

The IoT is enabling advances across multiple market sectors, but it is the Industrial IoT (IIoT) that is having the most impact. It is already the biggest IoT vertical and covers multiple types of projects across industry, from simple data collection to more complex projects incorporating just-in-time manufacturing and predictive quality control.

The biggest benefit of the IIoT is how it is creating innovative solutions to help manufacturers achieve their business objectives by delivering better services and products to their customers. There are three principle reasons for implementing an IIoT application – to make money, to save money, or to stay compliant – and sometimes all three can be delivered. Certainly, at Telit, we would not counsel anyone to consider investing in an IIoT project unless it meets one or more of those three objectives.

Data is the New Gold

A properly implemented IIoT should enable manufacturers to collect data from every step in the process. Every machine can and should produce data, and the processing of that data should deliver invaluable information that helps create more efficient processes and factories. Look back 10-15 years, and there was a big shift in production, with manufacturing operations leaving the U.S. and Europe for China because labor cost was the most important consideration.

The IIoT is set to have the same effect as labor costs; data is the new gold. Information from the IIoT will make manufacturers’ assets perform in a more cost-effective manner – so the better the data, the greater the improvements.

Let’s look at some examples of the transformational effect of the IIoT. One of the largest car vendors in the world implemented a replacement IIoT solution that significantly reduced latency in their systems.This reduction was so relevant that in just one plant it created 3,000 minutes more of uptime. This plant produces at a rate of about $30,000 per minute, so that’s an extra $90 million.

Additionally, integrating the solution operator by operator, line by line and shift by shift, there is now a continuous link between what is being produced and how it is being produced, increasing productivity and quality control. Based on the data gathered, the manufacturer achieved significant reductions in both set-up time and line downtime.

Global names like Mitsubishi and Honda rely on the IIoT to remotely connect sophisticated machinery with technicians and engineers who constantly check manufacturing performance levels, ensure preventative maintenance, and quickly react to any issues that may affect production. Chip giants utilize the IIoT to maintain top-level cybersecurity to protect its IPR from hackers. Multinational pharmaceutical companies use the IIoT to audit every step in the manufacture of their products to ensure full compliance with regulations and laws. 

The IIoT isn’t limited to high end manufacturing. Anything can be connected. In Brazil, the IIoT is used to transmit data about the condition of the sewer network and sends alerts to maintenance crews when cleaning is required. The IIoT can also be used to explain unusual behavior.

At a manufacturing plant In Mexico, an application measuring the productivity of each machine was able to show how one machine was producing less at night than during the morning and afternoon shifts. Upon investigation, it was revealed that the operator on the evening shift was leaving the machine on a regular basis – to chat with his girlfriend.

Manufacturers are embracing the technology and investing, and without needing to hire an army of software engineers to rewrite protocols. There are experts in the IoT space that can deliver guaranteed connectivity across all systems – reducing the implementation time to a couple of days.

The IIoT is changing the face of manufacturing, from predictive maintenance and supply chain management to condition monitoring. Yet only a fraction of the market potential has been explored so far. If you look at the Fortune 500, there isn’t one company that doesn’t have an IIoT application, but in most the technology is yet to permeate the whole organization.

There are huge untapped possibilities, and work to be done to achieve the true revolution that the IIoT promises. This applies not only to the actual manufacturing processes, but throughout the supply chain, leveraging connectivity for better traceability and quality control. The IIoT can, and will, touch, impact, and improve every step.

 

Ricardo Stefanato Buranello is the Global VP - IoT Factory Solutions for Telit, and has over 14 years of experience in the M2M/IoT industry. Buranello is responsible for Telit’s global factory solutions, which is a leading provider in industrial solutions for remote connectivity, edge logic automation, OT and IT integration.

 

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By AKHILESHSINGH SAITHWAR

The LLDP protocol is a Link Layer Discovery Protocol used by network devices to identify their neighbors and their capabilities.

If you want to integrate LLDP protocol in your Linux/Embedded system, there are mainly two open-source codes. The first is lldpd and the other is openlldp. When I needed to integrate the LLDP in my network device, I studied both open-source codes. I am writing this article hoping that it will be useful for others who also want to use LLDP open-source code in their systems or network devices.

Below are the key points which should be considered when selecting the LLDP open-source code.

1. License

License is an important point to consider when you want to integrate an open-source code in your application. The lldpd is published under ISC License, whereas the openlldp is published under GPL-2.0 License. The difference between two licenses is that the ISC License is more permissive than the GPL-2.0 License.

If you use GPL-2.0 licensed open-source code in your application, you need to publish the changes back to the community. In case of ISC License, it is not required to publish your changes back to community. Please note that the scope of the article does not cover the full licensing requirements. Please understand the license before using it in your project.

2. Active Community Support

When picking up open-source code, we should also make sure that the development is active for that code. The development and support in lldpd are more active than the openlldp. When writing this article, there are a total of 8 tags in openlldp and 54 tags in lldpd. This indicates how quickly bugs are fixed and new version is released in lldpd.

3. Supported Protocols

There are other protocols like LLDP to discover the network devices, for example EDP, CDP. When selecting the LLDP open-source code, one should also make sure that it supports other protocols as well. This will make sure that the network devices with other protocols are also discovered. Though I have not verified the protocols listed in the documentations, from the document I can say that the lldpd supports EDP, CDP, FDP, SONMP and the openlldp supports EDP, CDP, EVB, MED, DCBX, VDP.

4. Custom Interface Support

In most of the cases the LLDP would run on standard Ethernet Interface but in some specific cases it may require executing LLDP on non-Ethernet interfaces, like Serial or I2C. In this case, it would be very helpful if the open-source code supports other interfaces. Though both open-source code does not support custom interfaces, the lldpd at least have documentation on how to add the custom interfaces. Adding custom interfaces on openlldp may require more time to understand and implement than lldpd.

5. Multiple Neighbour Support

This is one of the most important features when selecting the LLDP open-source code. Multiple neighbour support is needed if you are supposed to capture more than one LLDP enabled neighbour (network devices) on the same interfaces. As per my understanding, this is very basic feature which should be supported in all LLDP code. But I was surprised to know that this feature is not available in openlldp. Multiple neighbour support is available in lldpd.

6. Daemon Configuration Tool

Daemon configuration tool helps to configure the LLDP parameters, get status, enable/disable interfaces. Both lldpd and openlldp has their configuration tools. The lldpd has lldpcli/lldpctl and the openlldp has lldptool for configuration.

7. LLDP Statistics

Both lldpd and openlldp supports display of interface and neighbour statistics through there configuration tools. The statistics includes Total Frame Outs, Total Error Frame Outs, Total Age Out Frames, Total Discarded Frames, Total Frame In, Total Frame In Errors, Total Discarded Error Frames, Total TLVs in Errors, Total TLV’s Accepted etc.

8. Custom TLV Support

Both the lldpd and openlldp supports reception and transmission of custom TLV’s. The custom TLV’s can be set or get using their configuration tools.

9. SNMP Agent

Both lldpd and openlldp supports SNMP agent.

Comparison table

Based on above points the below table is populated for comparison purpose. One can decide whether lldpd or openlldp should be used in their system or network devices.

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Conclusion

As per my opinion it is better to choose the lldpd open-source code over the openlldp considering the license, features and community support. The licensing of lldpd is more permissive than the open-lldp. There are more features in lldpd compared to open-lldp. The community support for lldpd is more active than the open-lldp. So unless you have direction from your client to use specific open source lldp package, go for lldpd. eInfochips has in-depth expertise in the areas of firmware design for embedded systems development. We offer end-to-end support for firmware development starting from system requirements to testing for quality and environment.

Originally posted here.

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by Evelyn Münster

IoT systems are complex data products: they consist of digital and physical components, networks, communications, processes, data, and artificial intelligence (AI). User interfaces (UIs) are meant to make this level of complexity understandable for the user. However, building a data product that can explain data and models to users in a way that they can understand is an unexpectedly difficult challenge. That is because data products are not your run-of-the-mill software product.

In fact, 85% of all big data and AI projects fail. Why? I can say from experience that it is not the technology but rather the design that is to blame.

So how do you create a valuable data product? The answer lies in a new type of user experience (UX) design. With data products, UX designers are confronted with several additional layers that are not usually found in conventional software products: it’s a relatively complex system, unfamiliar to most users, and comprises data and data visualization as well as AI in some cases. Last but not least, it presents an entirely different set of user problems and tasks than customary software products.

Let’s take things one step at a time. My many years in data product design have taught me that it is possible to create great data products, as long as you keep a few things in mind before you begin.

As a prelude to the UX design process, make sure you and your team answer the following nine questions:

1. Which problem does my product solve for the user?

The user must be able to understand the purpose of your data product in a matter of minutes. The assignment to the five categories of the specific tasks of data products can be helpful: actionable insights, performance feedback loop, root cause analysis, knowledge creation, and trust building.

2. What does the system look like?

Do not expect users to already know how to interpret the data properly. They need to be able to construct a fairly accurate mental model of the system behind the data.

3. What is the level of data quality?

The UI must reflect the quality of the data. A good UI leads the user to trust the product.

4. What is the user’s proficiency level in graphicacy and numeracy?

Conduct user testing to make sure that your audience will be able to read and interpret the data and visuals correctly.

5. What level of detail do I need?

Aggregated data is often too abstract to explain, or to build user trust. A good way to counter this challenge is to use details that explain things. Then again, too much detail can also be overwhelming.

6. Are we dealing with probabilities?

Probabilities are tricky and require explanations. The common practice of cutting out all uncertainties makes the UI deceptively simple – and dangerous.

7. Do we have a data visualization expert on the design team?

UX design applied to data visualization requires a special skillset that covers the entire process, from data analysis to data storytelling. It is always a good idea to have an expert on the team or, alternatively, have someone to reach out to when required.

8. How do we get user feedback?

As soon as the first prototype is ready, you should collect feedback through user testing. The prototype should present content in the most realistic and consistent way possible, especially when it comes to data and figures.

9. Can the user interface boost our marketing and sales?

If the user interface clearly communicates what the data product does and what the process is like, then it could take on a new function: sell your products.

To sum up: we must acknowledge that data products are an unexplored territory. They are not just another software product or dashboard, which is why, in order to create a valuable data product, we will need a specific strategy, new workflows, and a particular set of skills: Data UX Design.

Originally posted HERE 

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By Adam Dunkels

When you have to install thousands of IoT devices, you need to make device installation impressively fast. Here is how to do it.

Every single IoT device out there has been be installed by someone.

Installation is the activity that requires the most attention during that device’s lifetime.

This is particularly true for large scale IoT deployments.

We at Thingsquare have been involved in many IoT products and projects. Many of these have involved large scale IoT deployments with hundreds or thousands of devices per deployment site.

In this article, we look at why installation is so important for large IoT deployments – and a list of 6 installation tactics to make installation impressively fast while being highly useful:

  1. Take photos
  2. Make it easy to identify devices
  3. Record the location of every device
  4. Keep a log of who did what
  5. Develop an installation checklist, and turn it into an app
  6. Measure everything

And these tactics are useful even if you only have a handful of devices per site, but thousands or tens of thousands of devices in total.

Why Installation Tactics are Important in Large IoT Deployments

Installation is a necessary step of an IoT device’s life.

Someone – maybe your customers, your users, or a team of technicians working for you – will be responsible for the installation. The installer turns your device from a piece of hardware into a living thing: a valuable producer of information for your business.

But most of all, installation is an inevitable part of the IoT device life cycle.

The life cycle of an IoT device can be divided into four stages:

  1. Produce the device, at the factory (usually with a device programming tool).
  2. Install the device.
  3. Use the device. This is where the device generates the value that we created it for. The device may then be either re-installed at a new location, or we:
  4. Retire the device.

Two stages in the list contain the installation activity: both Install and Use.

So installation is inevitable – and important. We need to plan to deal with it.

Installation is the Most Time-Consuming Activity

Most devices should spend most of their lifetime in the Use stage of their life cycle.

But a device’s lifetime is different from the attention time that we need to spend on them.

Devices usually don’t need much attention in their Use stage. At this stage, they should mostly be sitting there and generate valuable information.

By contrast, for the people who work with the devices, most of their attention and time will be spent in the Install stage. Since those are people who’s salary you are paying for, you want to be as efficient as possible.

How To Make Installation Impressively Fast - and Useful

At Thingsquare, we have deployed thousands of devices together with our customers, and our customers have deployed many hundreds of thousands of devices with their customers.

These are our top six tactics to make installation fast – and useful:

1. Take Photos

After installation, you will need to maintain and troubleshoot the system. This is a normal part of the Use stage.

Photos are a goldmine of information. Particularly if it is difficult to get to the location afterward.

Make sure you take plenty of photos of each device as they are installed. In fact, you should include multiple photos in your installation checklist – more about this below.

We have been involved in several deployments where we have needed to remotely troubleshoot installations after they were installed. Having a bunch of photos of how and where the devices were installed helps tremendously.

The photos don’t need to be great. Having a low-quality photo beats having no photo, every time.

 

2. Make it Easy to Identify Devices

When dealing with hundreds of devices, you need to make sure that you know exactly which you installed, and where.

You therefore need to make it easy to identify each device. Device identification can be made in several ways, and we recommend you to use more than one way to identify the devices. This will reduce the risk of manual errors.

The two ways we typically use are:

  • A printed unique ID number on the device, which you can take a photo of
  • Automatic secure device identification via Bluetooth – this is something the Thingsquare IoT platform supports out of the box

Being certain about where devices were installed will make maintenance and troubleshooting much easier – particularly if it is difficult to visit the installation site.

3. Record the Location of Every Device

When devices are installed, make sure to record their location.

The easiest way to do this is to take the GPS coordinates of the devices as it is being deployed. Preferably with the installation app, which can do this automatically – see below.

For indoor installations, exact GPS locations may be unreliable. But even for those devices, having a coarse-grained GPS location is useful.

The location is useful both when analyzing the data that the devices produce, and when troubleshooting problems in the network.

 

4. Keep a Log of Who Did What

In large deployments, there will be many people involved.

Being able to trace the installation actions, as well as who took what action, is enormously useful. Sometimes just knowing the steps that were taken when installing each device is important. And sometimes you need to talk to the person who did the installation.

5. Develop an Installation Checklist - and Turn it into an App

Determine what steps are needed to install each device, and develop a step-by-step checklist for each step.

Then turn this checklist into an app that installation personnel can run on their own phones.

Each step of each checklist should be really easy understand to avoid mistakes along the way. And it should be easy to go back and forth in the steps, if needed.

Ideally, the app should run on both Android and iOS, because you would like everyone to be able to use it on their own phones.

Here is an example checklist, that we developed for a sensor device in a retail IoT deployment:

  • Check that sensor has battery installed
  • Attach sensor to appliance
  • Make sure that the sensor is online
  • Check that the sensor has a strong signal
  • Check that the GPS location is correct
  • Move hand in front of sensor, to make sure sensor correctly detects movement
  • Be still, to make sure sensor correctly detects no movement
  • Enter description of sensor placement (e.g. “on top of the appliance”)
  • Enter description of appliance
  • Take a photo of the sensor
  • Take a photo of the appliance
  • Take a photo of the appliance and the two beside it
  • Take a photo of the appliance and the four beside it
 

6. Measure Everything

Since installation costs money, we want it to be efficient.

And the best way to make a process more efficient is to measure it, and then improve it.

Since we have an installation checklist app, measuring installation time is easy – just build it into the app.

Once we know how much time each step in the installation process needs, we are ready to revise the process and improve it. We should focus on the most time-consuming step first and measure the successive improvements to make sure we get the most bang for the buck.

Conclusions

Every IoT device needs to be installed and making the installation process efficient saves us attention time for everyone involved – and ultimately money.

At Thingsquare, we have deployed thousands of devices together with our customers, and our customers have deployed many hundreds of thousands of devices with their customers.

We use our experience to solve hard problems in the IoT space, such as how to best install large IoT systems – get in touch with us to learn more!

Originally posted here.

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“Productivity isn’t everything, but in the long run, it is almost everything.” This well-known quote is attributed to Paul Krugman, the well-known American economist and winner of a Nobel Memorial Prize in Economic Sciences for his contributions to New Trade Theory and New Economic Geography.

In economic terms, a common definition of productivity cites it as the ratio between the volume of outputs and the volume of inputs. It measures the efficiency of production inputs – labor and capital – used to produce a given level of output.

 
For countries and companies alike, productivity gain is a fundamental goal. For countries, productivity leads to higher real income, which contributes to higher living standards and better social services.

For companies, productivity is a key driver of sustainable profits and competitiveness over time. The global economy, with open markets and wide competition, pushes companies for constant productivity gains. Companies that fail in the race for productivity are the perfect candidates for extinction in the near future.

 

Productivity can be boosted in a few different ways, most notably through the innovation of new products or through new business models that guarantee higher scalability and demand. One example is how Starbucks built a sustainable business model with high levels of productivity through the deployment of strong, intangible assets such as a unique brand and efficient business processes.

Another example is Apple, a company that executed its strategy to perfection, creating a legion of fans that constantly run to buy the company’s new products, and sometimes even camp overnight outside an Apple store to get a device before it sells out. Apple succeeded not only in designing some of the most desired smartphones and PCs on the market but also in creating a business platform that generates incremental service and software revenue on top of its products. In 2020, about 15% of Apple’s revenue came from services, leveraged by its platform strategy.

Another important factor in productivity is the innovation inside. That is, how to produce more with fewer resources. While in the past few decades industrial efficiency was boosted by moving factories to low labor cost economies, this recipe is getting exhausted. The cost increase in Asian countries, driven by higher salaries, geopolitical risks and the increase in automation levels is changing the balance of this equation.

In an environment of hyper-competition and open markets, technology is rapidly reshaping manufacturing. The companies that survive in this new paradigm will be those that adopt data-driven models, innovate on their products and services, and embrace the challenge of producing more with less. I believe IoT and Industry 4.0 will be the drivers of this transformation.

Start With Management

Everything starts with management. Managers need to embrace innovation and constant improvement. Processes need to be quantified, and efficiency ratios for each of the individual processes need to be measured. For example, overall equipment effectiveness (OEE) needs to be calculated per machine, line, operator, sector and plant. Such KPIs are important to enable managers to make real-time decisions.

Include Machines

If data-driven management is the goal, then it’s time to think about execution. The ability to collect data from a variety of different machines and from a variety of different vendors is a big challenge. Industrial machines in general don’t have a common protocol and as such, collecting the data in a highly efficient manner can be challenging and daunting.

Beyond connecting machines themselves, machine data needs to be efficiently integrated across different IT systems and software, such as manufacturing execution systems (MES), enterprise resource planning (ERP) software and a variety of database applications. On top of that, there comes the challenge of building and integrating higher-level functionality, such as edge logic for real-time actions, data visualization for operators and managers, data analytics, cloud computing, machine learning and the list goes on. The complexity and associated challenges of machine and data integration cause many companies to fail along the way.

Avoid The Custom Code Trap

Many companies fail in the execution, and one of the reasons is because it is not a simple task. As IIoT is a relatively new concept, the market is not fully matured. Many companies create their own internal team and start to code. The problem is companies may not be prepared – they often lack the right level of skills, people, and expertise. It's not impossible to execute internally, but oftentimes focusing on your core business and finding the best technology tools for your needs in the market is the more efficient choice.

If you're looking at outside teams, a good way to avoid high development costs and operations risk is to find an integrated platform that merges data collection, edge computing and information technology/operational technology (IT/OT) integration. The more vertically integrated, the faster the deployment and the less likely you will need "Band-Aids" to integrate systems. This will provide more flexibility and optimize performance while reducing the cost and risks of the project.

It’s also important to remember that innovation and productivity is more than a task. It is a journey. Processes need to constantly evolve, and your IIoT platform must provide the ability to be flexible when you need to change machines, systems, metrics and processes.

In the end, productivity excellence is a blend of management, creativity and technology. It means pushing people out of their comfort zone and augmenting possibilities with technology. Not easy, but certainly needed.

 

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by Stephanie Overby

What's next for edge computing, and how should it shape your strategy? Experts weigh in on edge trends and talk workloads, cloud partnerships, security, and related issues


All year, industry analysts have been predicting that that edge computing – and complimentary 5G network offerings ­­– will see significant growth, as major cloud vendors are deploying more edge servers in local markets and telecom providers pushing ahead with 5G deployments.

The global pandemic has not significantly altered these predictions. In fact, according to IDC’s worldwide IT predictions for 2021, COVID-19’s impact on workforce and operational practices will be the dominant accelerator for 80 percent of edge-driven investments and business model change across most industries over the next few years.

First, what exactly do we mean by edge? Here’s how Rosa Guntrip, senior principal marketing manager, cloud platforms at Red Hat, defines it: “Edge computing refers to the concept of bringing computing services closer to service consumers or data sources. Fueled by emerging use cases like IoT, AR/VR, robotics, machine learning, and telco network functions that require service provisioning closer to users, edge computing helps solve the key challenges of bandwidth, latency, resiliency, and data sovereignty. It complements the hybrid computing model where centralized computing can be used for compute-intensive workloads while edge computing helps address the requirements of workloads that require processing in near real time.”

Moving data infrastructure, applications, and data resources to the edge can enable faster response to business needs, increased flexibility, greater business scaling, and more effective long-term resilience.

“Edge computing is more important than ever and is becoming a primary consideration for organizations defining new cloud-based products or services that exploit local processing, storage, and security capabilities at the edge of the network through the billions of smart objects known as edge devices,” says Craig Wright, managing director with business transformation and outsourcing advisory firm Pace Harmon.

“In 2021 this will be an increasing consideration as autonomous vehicles become more common, as new post-COVID-19 ways of working require more distributed compute and data processing power without incurring debilitating latency, and as 5G adoption stimulates a whole new generation of augmented reality, real-time application solutions, and gaming experiences on mobile devices,” Wright adds.

8 key edge computing trends in 2021


Noting the steady maturation of edge computing capabilities, Forrester analysts said, “It’s time to step up investment in edge computing,” in their recent Predictions 2020: Edge Computing report. As edge computing emerges as ever more important to business strategy and operations, here are eight trends IT leaders will want to keep an eye on in the year ahead.

1. Edge meets more AI/ML


Until recently, pre-processing of data via near-edge technologies or gateways had its share of challenges due to the increased complexity of data solutions, especially in use cases with a high volume of events or limited connectivity, explains David Williams, managing principal of advisory at digital business consultancy AHEAD. “Now, AI/ML-optimized hardware, container-packaged analytics applications, frameworks such as TensorFlow Lite and tinyML, and open standards such as the Open Neural Network Exchange (ONNX) are encouraging machine learning interoperability and making on-device machine learning and data analytics at the edge a reality.” 

Machine learning at the edge will enable faster decision-making. “Moreover, the amalgamation of edge and AI will further drive real-time personalization,” predicts Mukesh Ranjan, practice director with management consultancy and research firm Everest Group.

“But without proper thresholds in place, anomalies can slowly become standards,” notes Greg Jones, CTO of IoT solutions provider Kajeet. “Advanced policy controls will enable greater confidence in the actions made as a result of the data collected and interpreted from the edge.” 

 

2. Cloud and edge providers explore partnerships


IDC predicts a quarter of organizations will improve business agility by integrating edge data with applications built on cloud platforms by 2024. That will require partnerships across cloud and communications service providers, with some pairing up already beginning between wireless carriers and the major public cloud providers.

According to IDC research, the systems that organizations can leverage to enable real-time analytics are already starting to expand beyond traditional data centers and deployment locations. Devices and computing platforms closer to end customers and/or co-located with real-world assets will become an increasingly critical component of this IT portfolio. This edge computing strategy will be part of a larger computing fabric that also includes public cloud services and on-premises locations.

In this scenario, edge provides immediacy and cloud supports big data computing.

 

3. Edge management takes center stage


“As edge computing becomes as ubiquitous as cloud computing, there will be increased demand for scalability and centralized management,” says Wright of Pace Harmon. IT leaders deploying applications at scale will need to invest in tools to “harness step change in their capabilities so that edge computing solutions and data can be custom-developed right from the processor level and deployed consistently and easily just like any other mainstream compute or storage platform,” Wright says.

The traditional approach to data center or cloud monitoring won’t work at the edge, notes Williams of AHEAD. “Because of the rather volatile nature of edge technologies, organizations should shift from monitoring the health of devices or the applications they run to instead monitor the digital experience of their users,” Williams says. “This user-centric approach to monitoring takes into consideration all of the components that can impact user or customer experience while avoiding the blind spots that often lie between infrastructure and the user.”

As Stu Miniman, director of market insights on the Red Hat cloud platforms team, recently noted, “If there is any remaining argument that hybrid or multi-cloud is a reality, the growth of edge solidifies this truth: When we think about where data and applications live, they will be in many places.”

“The discussion of edge is very different if you are talking to a telco company, one of the public cloud providers, or a typical enterprise,” Miniman adds. “When it comes to Kubernetes and the cloud-native ecosystem, there are many technology-driven solutions competing for mindshare and customer interest. While telecom giants are already extending their NFV solutions into the edge discussion, there are many options for enterprises. Edge becomes part of the overall distributed nature of hybrid environments, so users should work closely with their vendors to make sure the edge does not become an island of technology with a specialized skill set.“

 

4. IT and operational technology begin to converge


Resiliency is perhaps the business term of the year, thanks to a pandemic that revealed most organizations’ weaknesses in this area. IoT-enabled devices (and other connected equipment) drive the adoption of edge solutions where infrastructure and applications are being placed within operations facilities. This approach will be “critical for real-time inference using AI models and digital twins, which can detect changes in operating conditions and automate remediation,” IDC’s research says.

IDC predicts that the number of new operational processes deployed on edge infrastructure will grow from less than 20 percent today to more than 90 percent in 2024 as IT and operational technology converge. Organizations will begin to prioritize not just extracting insight from their new sources of data, but integrating that intelligence into processes and workflows using edge capabilities.

Mobile edge computing (MEC) will be a key enabler of supply chain resilience in 2021, according to Pace Harmon’s Wright. “Through MEC, the ecosystem of supply chain enablers has the ability to deploy artificial intelligence and machine learning to access near real-time insights into consumption data and predictive analytics as well as visibility into the most granular elements of highly complex demand and supply chains,” Wright says. “For organizations to compete and prosper, IT leaders will need to deliver MEC-based solutions that enable an end-to-end view across the supply chain available 24/7 – from the point of manufacture or service  throughout its distribution.”

 

5. Edge eases connected ecosystem adoption


Edge not only enables and enhances the use of IoT, but it also makes it easier for organizations to participate in the connected ecosystem with minimized network latency and bandwidth issues, says Manali Bhaumik, lead analyst at technology research and advisory firm ISG. “Enterprises can leverage edge computing’s scalability to quickly expand to other profitable businesses without incurring huge infrastructure costs,” Bhaumik says. “Enterprises can now move into profitable and fast-streaming markets with the power of edge and easy data processing.”

 

6. COVID-19 drives innovation at the edge


“There’s nothing like a pandemic to take the hype out of technology effectiveness,” says Jason Mann, vice president of IoT at SAS. Take IoT technologies such as computer vision enabled by edge computing: “From social distancing to thermal imaging, safety device assurance and operational changes such as daily cleaning and sanitation activities, computer vision is an essential technology to accelerate solutions that turn raw IoT data (from video/cameras) into actionable insights,” Mann says. Retailers, for example, can use computer vision solutions to identify when people are violating the store’s social distance policy.

 

7. Private 5G adoption increases


“Use cases such as factory floor automation, augmented and virtual reality within field service management, and autonomous vehicles will drive the adoption of private 5G networks,” says Ranjan of Everest Group. Expect more maturity in this area in the year ahead, Ranjan says.

 

8. Edge improves data security


“Data efficiency is improved at the edge compared with the cloud, reducing internet and data costs,” says ISG’s Bhaumik. “The additional layer of security at the edge enhances the user experience.” Edge computing is also not dependent on a single point of application or storage, Bhaumik says. “Rather, it distributes processes across a vast range of devices.”

As organizations adopt DevSecOps and take a “design for security” approach, edge is becoming a major consideration for the CSO to enable secure cloud-based solutions, says Pace Harmon’s Wright. “This is particularly important where cloud architectures alone may not deliver enough resiliency or inherent security to assure the continuity of services required by autonomous solutions, by virtual or augmented reality experiences, or big data transaction processing,” Wright says. “However, IT leaders should be aware of the rate of change and relative lack of maturity of edge management and monitoring systems; consequently, an edge-based security component or solution for today will likely need to be revisited in 18 to 24 months’ time.”

Originally posted here.

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By Natallia Babrovich

My experience shows that most of the visits to doctors are likely to become virtual in the future. Let’s see how IoT solutions make the healthcare environment more convenient for patients and medical staff.

What are IoT and IoMT?

My colleague Alex Grizhnevich, IoT consultant at ScienceSoft, defines Internet of Things as a network of physical devices with sensors and actuators, software, and network connectivity that enable devices to gather and transmit data and fulfill users' tasks. Today, IoT becomes a key component of the digital transformation of healthcare, so we can distinguish a separate group of initiatives, the so-called IoHT (Internet of Health Things) or IoMT (Internet of Medical Things).

Popular IoMT Use Cases

IoT-based patient care

Medication intake tracking

IoT-based medication tracking allows doctors to monitor the impact of a prescribed medication’s dosage on a patient’s condition. In their turn, patients can control medication intake, e.g., by using in-app reminders and note in the app how their symptoms change for their doctor’s further analysis. The patient app can be connected to smart devices, (e.g., a smart pill bottle) for easier management of multiple medications.

Remote health monitoring

Among examples of employing IoT in healthcare, this use case is especially viable for chronic disease management. Patients can use connected medical devices or body-worn biosensors to allow doctors or nurses to check their vitals (blood pressure, glucose level, heart rate, etc.) via doctor/nurse-facing apps. Health professionals can monitor this data 24/7 and study app-generated reports to get insights into health trends. Patients who show signs of deteriorating health are scheduled for in-person visits.

IoT- and RFID-based medical asset monitoring

Medical inventory and equipment tracking

All medical tools and durable assets (beds, medical equipment) are equipped with RFID (radio frequency identification) tags. Fixed RFID readers (e.g., on the walls) collect the info about the location of assets. Medical staff can view it using a mobile or web application with a map.

Drug tracking

RFID-enabled drug tracking helps pharmacies and hospitals verify the authenticity of medication packages and timely spot medication shortages.

Smart hospital space

Cloud-connected ward sensors (e.g., a light switch, door and window contacts) and ambient sensors (e.g., hydrometers, noise detectors) allow patients to control their environment for a comfortable hospital stay.

Advantages of using IoT technology in healthcare

Patient-centric care

Medical IoT helps turn patients into active participants of the treatment process, thus improving care outcomes. Besides, IoMT helps increase patient satisfaction with care delivery, from communication with medical staff to physical comfort (smart lighting, climate control, etc.).

Reduced care-related costs

Non-critical patients can stay at home and use cloud-connected medical IoT devices, which gather, track and send health data to the medical facility. And with the help of telehealth technology, patients can schedule e-visits with nurses and doctors without traveling to the hospital.

Reduced readmissions

Patient apps connected to biosensors help ensure compliance with a discharge plan, enable prompt detection of health state deviations, and provide an opportunity to timely contact a health professional remotely.

Challenges of IoMT and how to address them

Potential health data security breaches

The connected nature of IoT brings about information security challenges for healthcare providers and patients.

Tip from ScienceSoft

We recommend implementing HIPAA-compliant IoMT solutions and conduct vulnerability assessment and penetration testing regularly to ensure the highest level of protection.

Integration difficulties

Every medical facility has its unique set of applications to be integrated with an IoMT solution (e.g., EHR, EMR). Some of these applications may be heavily customized or outdated.

Tip from ScienceSoft

Develop the integrations strategy from the start of your IoMT project, including the scope and the nature of custom integrations.

Enhance care delivery with IoMT

According to my estimates, the use of IoT technology in healthcare will continue to rise during the next decade, driven by the impact of the COVID situation and the growing demand for remote care. If you need help with creating and implementing a fitting IoMT solution, you’re welcome to turn to ScienceSoft’s healthcare IT team.

Originally posted here.

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 Over the years, IoT has made its way into the complex consumer markets and made millions of lives easier and smarter. Without a doubt, the industry holds enormous potential for upcoming entrepreneurs to introduce innovative solutions. In fact, the number of IoT start-ups have grown by 27% from 2019 till mid-2020.

 

While many of these IoT projects have made the cut, others are struggling to realize the intended RoI. Although tempting but it still a highly challenging space to be in and create sustainable companies. 

 

While a new organization is a collaborative effort of many people, it is the leaders who hold the vision strong and spearhead the transformation. For those setting on their journeys of tech start-ups, here’s what you can learn from the best.

 

Targeting the right KPIs 

The rule to achieve your KPIs is simple – never ignore them. Start-ups who planned around the KPIs were able to meet them quickly and seamlessly. Starting from product ideation to distributing the budgets across marketing, development and acquiring customers and retaining them, the complete lifecycle should be evaluated periodically through metrics such as Customer Acquisition Cost (CAC), Customer Retention Rate (CRR) and the Life-Time Value (LTV).

Customer Retention Rate (CRR) is the total number of customers a business is able to retain over a given period of time. High retention rates are a clear hint of a successful product and a fully satisfied customer while high attrition rates mean the opposite. Life Time Value (LTV) is the net value of a customer to the business. When these metrics are evaluated in relation to each other such as the LTV/CAC ratio, the total capital efficiency of a company can be predicted.

IoT enables you to take a step further in tracking KPIs:

  • Track end usage using IoT and deduce usage analytics.
  • Take user feedback at the point of usage using IoT and deduce user experience in real-time.
  • Use remote device management to monitor the health of your IoT solution and run diagnostics to find and fix issues. This will help in keeping MTTr rate (Mean Time to Repair) as controlled as possible.

These advanced indicators can directly help you in reducing expenses and increase revenues by improving customer experience.  



Why are these important? Entrepreneurs who stayed intact to meet these KPIs have seen a 10x increase in business efficiency. This is an important takeaway for budding entrepreneurs who have to justify their investments periodically. Since CAC has increased by 50% over the past few years, not ignoring performance KPIs is the foremost lesson for every new leader. 

 

Rapid adoption to change

IoT is not the same as it was 5 years ago. In fact, it may not be a ‘new technology on the block’ anymore. It is continuously evolving and start-ups have no choice but to keep experimenting with newer builds and processes. For example, embracing new technologies such as Edge computing or bringing anonymity to the data transfers, IoT products must upgrade. Likewise, project owners can improvise their development process by officially collaborating with other companies. It is a mesh and more hands will help to simplify. So be it outsourcing the resourcing requirements to a partner or outsourcing end-to-end product development, start-ups must weigh their choices and utilize the available expertise optimally.  

 

Few entrepreneurs have been able to resolve this complexity by trekking the midline. They sensed that the risk of not embracing change is greater than the risk of failing. Therefore, budding entrepreneurs must understand that experimentation doesn’t have to replace your existing processes. It can be an additional vertical which is committed to embracing contemporary product offerings or technologies. 


Despite the world being restricted indoors due to Covid, the following tech entrepreneurs have brilliantly led their workforce and achieved impressive results. 

 

Yevgeny Dibrov
CEO Armis Security

Armis Security ventured, attempted and mastered a market that most companies are scared of trying – IoT cybersecurity. Led by the hugely ambitious Yevgeny Dibrov, Amris is a security platform that discovers devices across the network, analyses their behaviors and identifies risks. For an industry plagued with cybersecurity threats, Amris is a huge reassurance. The company has a line-up of customers across sectors such as healthcare, automobile, finance and manufacturing.

While the start-up completes 5 years shortly, CEO Yevgeny quotes – “ "As companies accelerate their digital transformation initiatives, securely enable employees to work from home long-term, and adopt 5G, we are seeing an explosion of connected devices. At the same time, this uptick has increased the risk profile for businesses, especially around ransomware attacks, which is driving even more demand for our industry-leading agentless device security platform”.

 

Daniel Price
CEO - Ioterra Inc.

When most start-ups were swaying in the hype of IoT, Ioterra foresaw the complications and immediately plunged at the opportunity to resolve a huge gap in the IoT ecosystem – the challenge of quickly sourcing reliable IoT service partners and other resources needed for a successful IoT initiative. Unlike other technology markets, IoT is a rare space that involves sourcing complications regarding IoT services as well as solutions from all walks of technology – hardware, software and wireless communications. Besides delaying projects, sourcing difficulties lead to cost overheads. As an IoT consultant himself, Daniel along with his team created a digital marketplace that enables project owners to seek sourcing assistance based on their business model, type and sector. 

Daniel says, “Startups are advised to ensure a minimum of 12-18 months of runway. The most important reasoning behind this thinking is that you would invariably pivot 2-3 times before you get it right and you need to survive until then. Unless you watch the KPIs regularly and quickly pivot adapting to what you see on the ground, you cannot build a growing startup”.

 

Amir Haleem
CEO - Helium

Technologies from all sectors and markets have started to embrace Web 3.0 and Helium is IoT’s big bet. It is a platform that empowers businesses to develop connectivity for devices and sensors over a peer-to-peer wireless network. CEO Amir Haleem who was always ambitious about wireless coverage for low power IoT devices aims at bringing more projects on the stage.

He quotes - We’ve worked hard to bring native geo-location to everything that connects to the network. This opens up all sorts of interesting use cases that haven’t been seen yet, which have otherwise been impossible to build.

 

What’s common in all of them?- The Ethos to grow 

Ultimately, no start-up can grow without the mindset to win. Although most tech leaders ensure a learning culture within the organization, the motivation is mostly missing at the employee level. This largely happens when leaders don’t communicate their vision to the workforce and keep them restricted to the task assignments. The ethos to grow has to reflect at the individual level and that’s the hack to organizational success that many don’t get right.

Moreover, the missing KPIs and not retrospecting upon those failures along with your teams is a big flaw. In a startup environment wherein the team structure is mostly lean, the entrepreneurs must share quarterly progress with everyone. Besides keeping everyone in unison about the expected outcomes, such sessions float innovative ideas to achieve the results more efficiently. Therefore, upcoming entrepreneurs should ensure a work culture that acknowledges creative inputs. 

Motivated employees with a growth mindset, diligent tracking of KPIs and quick adaptability to change lay a solid foundation for success.

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