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The advent of Industry has marked the rise of IoT - the Internet of Things as one of the most significant shifts in the global devices market. It refers to the use of internet connectivity among the electric devices and systems to execute a joint function autonomously. 

 

We can find an uncanny resemblance to this concept in the movie Home Alone 4 (2002), where the idea of a smart home fad was beautifully narrated with its pros and cons that will turn into a reality soon. Two decades down the line, we are on the brink of the IoT revolution, which will result in increasing the living standards globally. Dive in deeper to explore the current happenings and future horizons.

 

Current Market Scenario and the Probable Stakeholders

The potential of IoT applications is widely recognized by both enterprises, retail consumers, and government agencies as it will integrate the cyber-physical systems with internet connectivity in order to interact with the surrounding through sensors and manipulating devices. Business Insider estimates the value of this tech innovation to be $1.7 trillion in the year 2019. The use of the Internet of Things will reduce the need for human effort in various tasks and provide controlled environments for achieving the desired results. 

 

The investment done by the tech giants is illustrated in the below figure:

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 (source: Forbes)

 

Some Famous User Cases Which are Expected to Take off Exponentially

Manufacturing Sector

The companies like ABB, Airbus, Shell, and the long-term IoT pioneer Caterpillar have been proactively pushing for such innovations in building safer workplaces that require fewer human interactions in hazardous work, which is also beneficial to the profitability of the business. It will also find great reception in predictive maintenance scheduling and inventory management. 

 

Asset Management

The businesses are looking forward to replacing the GPS in order to increase the efficiency of tracking company-owned devices through internet connectivity. This will also reduce the lags in logistics and provide accurate details for the consumables, as in the case of printers. Another example would be integrating the payroll software with the employee vehicles to reimburse traveling claims.

 

Agriculture 

The use of IoT to develop smart greenhouse farms with autonomous controlled environments will prove to be a boon for the agriculture industry as it will help in boosting crop production. Smart irrigation will control the soil quality, moisture content, atmospheric gas contents, and monitor plant health without any human intervention. The farm equipment will also be controlled in greenhouse farms with minimal need for human support.

 

Smart Homes

They are one of the largest areas where the revolution is expected to unravel the disruption in the electronic devices market. Google Nest, Ecobee, and Netatmo being the big fishes in the business. Everything including from your regular home appliances like fridge, television, ambiance and temperature control system, music system, and utilities are connected over the internet and controlled by remote servers. The user can interact with them using their smartphones. The house security is also connected with the central system. 

 

The effect on Living Standards

When we look at the current scenario, many of these tasks, when automated, the people currently dealing with hazards related to their respective fields such as heavy machinery or agriculture can work in a much more safer environment. Smart homes will increase the quality of life and help households in saving money since energy consumption is streamlined while providing a luxurious experience. Businesses will experience higher profitability and increased morale of the employees owing to the techno-savvy environment. 

 

The Development of Newer Devices through Prototyping 

Before the application is made, it is essential to test the reliability of all the devices since they will be used under different conditions and other manufacturer’s devices too. Also, the addition of newer devices shall also be considered. The use of prototypes in test conditions will prove to be an economical alternative to full-fledged testing. This will include the use of sensors and motion actuation systems with minimal cosmetic additions and cladding.  

The following considerations will affect the development of future-ready electronic gadgets compatible with IoT applications:

  • Safety against web-based third-party cyber attacks.
  • Modularized designs with programmable memories.
  • Standardization of source code libraries to facilitate interoperability.
  • Confirmation of regional government regulations.
  • Operational conditions.

The modern tech innovations such as AI, Cloud Computing, Blockchain, and the dawn of 5G connectivity will push the IoT movement along with the use of advanced sensors. Increased computing capacities will also contribute to data processing functionalities. However, the stakeholders in the industry ranging from vendors to maintenance personnel will have to cope with the advances in the technological aspects. The Internet of Things is also expected to be backed by academic institutions by covering it in the syllabi for creating a skilled workforce.

The author would also like to discuss the threats associated, which would pose a danger for the users. If the security provided isn’t adequate, ransomware attacks, stealing user information, altering device settings to provoke hazardous conditions are some of the worst-case scenarios. Hence, the vendors shall be conscientious about the security aspects along with the legal repercussions. 

 

Your Piece of the Pie 

A lot of new facilities and value additions to the existing devices and tools will boost the quality of human life, curb the problems caused due to the dangerous working conditions along with the health problems caused by them. It will find a broad spectrum of business domains, including smart cars to intelligent healthcare that will radically redefine our homes and workplaces alike.

The real potential is yet to be explored since the number of gadgets and tools is increasing day by day in each aspect of life. Be it economic or social backdrops, we will experience cost-optimization going hands in hands with unparalleled convenience, which is a rare phenomenon so far. We can also expect the Internet of Things crossing paths with other advanced technologies such as Artificial Intelligence, Big Data Analytics, and Edge Computing that will add value to their purpose in an exponential manner. 

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“We won't stop until we see every vehicle on the road being electric,” said Elon Musk, the person who works to revolutionize transportation both on earth and in space. “China is about to ban the internal combustion engine,” said a mining financier, Robert Friedland. Tesla Model 3 needs approximately 65 kilograms of copper per vehicle. Cities are now demanding zero-emission buses. Whether it’s electric cars, buses, trucks, solar energy or wind energy generation – as we transit to a sustainable world, we need more copper, nickel, cobalt, lithium, platinum, palladium, zinc and aluminum. That’s why, mining products will be in huge demand. Nevertheless, in the present world, these minerals and other mining products are already a backbone for most industries.

However, just because mining products are vital to run industries and build a low-carbon future, it doesn’t mean that the society should turn a blind eye to the damages caused due to mining operations.

Concerns from communities and governments regarding the environmental effects of digging up the earth to extract metals and minerals is battering the sector. Also, current investors have become restless and new investors are reluctant to finance mining activities as mining operations have not altered significantly since decades. This puts pressure on mine owners to bring a change in traditional mining practices. Such a situation drives many mine owners to bring data-driven practices into their routine mining operations.

Like most industries, the technology that disrupts the traditional ways of mining will be a significant driver of change in mining. The goal is to make mining more effective, sparing, energy intensive and environmental-friendly.

From decades, the mining industry has been deploying PLC and SCADA systems for monitoring and controlling. But these monitoring and control systems are generally proprietary systems and offer limited interoperability with other systems. This is where IoT-based systems prove to be advantageous. IoT-based systems are based on open and highly connected Internet Protocol (IP) network structure. Such open network architectures enable current mining operations to move toward the next generation of smart mining.

Let's look at how IoT implementation empowers mine owners with its ability to transform traditional mining practices and:

Say NO to carelessness

Since the advent of mining, fires and explosions are serious safety issues. Specifically, in coal mines, spontaneous coal seam combustion turns into a catastrophe mainly due to carelessness. Besides, in the biggest coal producer nation like China, approximately 25.1% of their main coal mines are extremely gaseous mines, which after burning could lead to a disaster. Also, the environment surrounding mines can be vulnerable during combustion as massive quantities of toxic gases, including CO2, CO, SO2 and H2S, are emitted when a mine catches fire. Therefore, prevention and protection from fires is important for secured mining production as well as the global environment.

The mechanism of spontaneous combustion of the coal seam is like a typical spontaneous combustion, which requires oxygen. Hence, measuring the concentration of O2 is the key. In addition to O2, other gas contents, such as CO, CO2, N2, CH4, C2H4, C2H6, Rn and so forth, can be evaluated to detect spontaneous coal combustion at the surveillance spot.

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As shown in the image above, an IoT-based system continuously monitors the sensed values and displays them to remote users through a web dashboard. Besides, the system can send alerts to such users in the case of detecting abnormal values and it can activate mitigation devices (e.g., forced ventilation) to decrease gas concentrations smartly.

Say NO to waste of resources

There is an increasing demand of mining products, mining equipment and resources – such as conveyors, shearers, boring machines, hydraulic pump stations, hydraulic support stations, crushers, loaders, motor vehicles, water pumps and ventilation fans – to run mining operations continuously. Moreover, to increase profitability form the existing resources, mine owners need an effective and safe resource management platform that can bring resource wastage time to zero. In such situations, an IoT network can help mine owners or managers to know the locations of these expensive resources and its usage statistics. Further, the underground staff can also be monitored via an IoT network.

Dundee Precious Metals sets the best example for this. They have deployed nearly 280 wireless access points over 50 km (31 miles) of tunnels in their flagship gold mine placed in Chelopech, Bulgaria. The firm quadrupled production from 0.5 million to 2 million tons by using an IoT-based system to track miners and vehicles locations, monitor vehicles status and automate safety and maintenance operations.

An IoT-based system is not only helpful to mine owners but original equipment manufacturers (OEMs) as well. The open connectivity of IoT architecture enables OEMs to monitor their product performance in their lifetime, even after the product is sold. Such data can be used to initiate a new revenue stream and to improve product design as well.

Say NO to casualties

In the case of a calamity, miners are taught to escape from the mine first with handy self-rescue equipment and enter a refuge alternative when escaping is cut off. Refuge alternatives are designed to provide 96 hours of breathable air, food and water for underground staff. Although refuge alternatives are only planned for use in post-accident occurrences, so their functionality should be checked periodically to ensure that they are working as intended in an emergency. In addition, a system should be in place to signal the surface instantly when a refuge alternative is triggered after a calamity. One way to monitor a refuge alternative's feasibility status from the ground is to attach sensors, such as a magnetic switch sensor, air quality and temperature sensors to the door of a refuge alternative. These sensors detect the occupancy status, air quality and temperature to ensure that a refuge alternative always stays safe.

To sum up, whether you need to cut expenses, lessen downtime, increase productivity or reduce environmental footprint – an IoT-based system is the right choice.

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The fact that the Internet of Things technology is the future of robotics and the digital industry as a whole is far from news. And here, how blockchain will help it develop is the most relevant, hot and promising topic of the current time. So, how will blockchain help build intelligent information exchange systems?

How the Internet of Things Works

In a nutshell, the “Internet of Things” (IoT) is such a concept of the internal network for household devices and items. A kind of chat or messenger for coffee makers, washing machines, vacuum cleaners, refrigerators, and even cars, thanks to which they can exchange data on the external environment.

Hundreds of smart people around the world are struggling to create a language that will teach everyday objects to communicate with each other. And, it seems that the blockchaindevelopment by app development companies is of little use here. But this is only at first glance.

In particular, IBM is developing this concept. Combining the two concepts is supposed to help:

• track and record all changes in the network;
• create special magazines with the entire history of changes;
• Define a smart contract system for data transfer.

Blockchain, in this case, would help to unite several devices into a single infrastructure. They would thus be able to exchange parts of the property - for example, data or currency. At the same time, the blockchain itself can be used to track the time of transactions at any time.

What do the experts think?

IBM conducted a special survey among IT industry professionals to find out how promising they find blockchain technology concerning the concept of the “Internet of things”.

However, this is the main property of any blockchain, wherever it is used. In the "Internet of things" you can also adjust the level of control over the device: weaken or strengthen. Using the blockchain in this way, you can reduce the risks of hacker attacks on the data exchange system.

Dell, represented by its specialist Jason Compton, believes that blockchain could become an alternative to traditional security systems. Decentralized control will allow you to expand the scheme and make it more easily scalable - that is, you will not have to build a multi-level expensive infrastructure with secure servers that the devices would have to access to exchange data. You can connect them to a peer-to-peer network directly and in any quantity you like.

Blockchain is not only for security

Using distributed registry technologies for IoT devices can not only solve security issues but also add new features and reduce operating costs. Blockchain is a technology that works with transactions and provides interaction in the network. It is great for monitoring processes in IoT.

For example, based on the blockchain, you can support the identification and discovery of devices, facilitate microtransactions between them, and provide proof of payment.

Ways to use the blockchain for the “Internet of things”

There are at least four areas in which the blockchain can be integrated into IoT:

• Creation of a trusting environment;
• Cost-saving;
• Acceleration of transactions;
• Security Improvement.

By the way, they are already working on these technologies to use them in the development of “smart equipment” or its individual components.

Examples of solutions of blockchaindevelopment for IoT

A typical example is the support by the Hyundai industrial corporation of a startup using blockchain technology. The project was called HDAC (Hyundai Digital Asset Currency) and at the end of November 2017 raised about $40 million for development.

The essence of technology that Hyundai is developing is to adapt the blockchain for its own IoT devices. The consensus protocol will unite all devices and act on the principle of smart contracts for the exchange of transactions.

Another company, Filament, is developing an industrial chip for IoT that will automatically encode sensor data and then adapt it for the blockchain. Thus, the exchange of information from the external environment between various equipment in a peer-to-peer decentralized network will be achieved.

The third characteristic example is the IOTA project, which uses the innovative blockchain - Tangle, designed specifically for IoT devices. At the same time, MIOTA tokens are traded on the cryptocurrency market and have impressive capitalization, representing value for investors.

It is worth recognizing that the development of the blockchain for the Internet of things is still far from implementation. In particular, several security-related issues have not yet been resolved, and some legal issues have not been addressed. However, the potential from the interaction of IoT and blockchain is truly enormous.

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The future of application is all set with the automation and intelligent technologies on the frontline for a vital change. Artificial Intelligence and the Internet of things are changing the course of the future of application development and automating the process capabilities and testing methods.

There are over 3 million smartphones in 2019 and the said number will almost surpass 3.8 million by 2021 and it is the indicator of widespread smartphone reach and a growing market for applications that are the source of revenue for several enterprises and businesses around the world today. This is why deploying AI for app development can improve app revenues.

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Development of mobile application has many stages in its development lifecycle and automation of these phases can render fruitful results for the developers, with greater reusability of the codes, seamless APIs and adaptive integration of user data to create user experiences that will be more intelligent.

Another important aspect of Artificial Intelligence-driven application development will be helpful in the integration of the Internet of Things based smart devices with the APIs of mobile devices. We have already seen the use of AI for smart features that have invoked smartphone markets with a frenzy.

Realization of Automation in Apps Development:

The application development lifecycle has several stages and substages. Putting it in a simple perspective there are three basic stages to be considered-Design, Deployment, and Testing. Automation of these stages was realized due to several challenges related to these stages. 

Designing the application optimized for the user experiences is quite a challenge as there are platform constraints and making the user interface seamlessly to facilitate the interaction between user and system smooth takes error-free programming. This is where automating the process can solve key issues with the design of applications.

Deployment and integration of newer versions of the applications with the already existing app versions without hindering the performance of the existing interface is a key challenge and here machine learning and NLP(Natural Language Program) techniques from the AI realm can automate the deployment to ensure continuous development and integration.

And Finally testing an application is one of the most challenging factors in an app development process. Automation of testing the application can bring effective performance enhancements that earlier were not realized and simulation of vital app functions and attributes can be achieved through the automation of the testing process.


Artificial Intelligence and IoT Realm: 

Artificial Intelligence is the ultimate keyword today for businesses worldwide. It is reported that AI will contribute up to $15.7 trillion by 2030 to the global business revenue. Similarly, the Internet of Things has shown quite a potential in the market that could induce $4 trillion to $11 trillion in economic value by 2025. The realm of AI and IoT may seem complex and segregated but they are quite intertwined and inclusive.

Leveraging the realm of AI and IoT can change the whole scenario of mobile application development. A mobile application has gained huge traction as a business and the enterprises and businesses are looking to structure their processes to align with the AI and IoT technologies. With IoT powering new markets like wearables and Augmented reality, the development of applications that can align its UI with these devices can be a challenging job. 

Another key aspect is the personalization of mobile applications, as the markets are envisaging the IoT based technologies, the personalization factor is gaining traction and AI can help applications achieve greater personalization through data analytics and machine learning techniques.


Three Stages Of Automated App Development:

1. Design:

Designing an application is the integration of ideation into the application interface to project the vision, mission, and functions of any idea. Any application that is developed with a simple function at its core is data that is transferred to and fro between the system and the user to help solve a problem of the user.

User Interface design should be efficient enough to solve a particular pre-defined problem. But, AI can help build an application that can use features like predictive analysis according to the data analytics and transform the UI according to the user data and bring about the user experience that can change the whole design paradigm.

Continuous analysis of data collected with each user interaction with the system is recorded, stored and analyzed through the data analytics and computational powers of intelligent machines to automate the altercations in the application designs.

2. Deployment:

Deployment of the application with cross-platform capabilities to capitalize on the environment of a particular platform through a single logical code for several devices and platforms can provide enhanced UX across all the platforms without hassle of changing the code each time.

Continuous Integration:

Continuous integration allows the android developers to submit small segments of the application each time. These codes are then saved and automatically dent to the build server immediately or sometimes at a definite regular interval. The build formed of these codes is then passed to an AI-based test server, which conducts tests of an application.

Integrations of several attributes of applications based on the user feedback achieved during the pre-production and prototyping phases along with the updates and the latest version integration of the applications can be automated through the machine learning algorithms and NLP.

Continuous Delivery:

Continuous Delivery can be considered as a collection of best practices designed to ensure rapid and safe deployment of code by delivering several changes to a production environment. It is followed by rigorous automated testing techniques to ensure full services and functionalities of a business application.

Using Predictive Analytics to make adjustments to the algorithms that can control the production phase of an application and based on the same make vital changes in the applications. Commonly, the application itself understands how to apply its rules based on how those rules have worked in the past.  

Continuous Deployment:
To ensure Continuous Deployment(CD) of the application through several phases and versions without too much effort and programming can be achieved through the use of machine learning capabilities. Continuous Deployment is considered as an extension of the continuous delivery and it differs from the delivery part with every change in the code. These changes that are passed through the automated testing phase is automatically included in the production phase.

3. Testing:

Automation of testing can reduce the regression cycles of any development team. Regression cycles can not only put pressure on the development team but also led to financial crisis and missed release deadlines. Testing of mobile applications can cause a prolonged regression cycle that involves different platforms and devices and it fails to keep up with the frequent updates of operating systems, and devices that are constantly introduced in the market. 


Deploying AI-based Continuous Testing Mechanism:

Achieving continuous application testing through AI-based mechanism can be achieved using machine learning by applying AI techniques to automatically learn the testing data without explicit programming. Further, this mechanism can access the data, run tests and apply the learning to testing cycles to make improvements.

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Machine learning can derive data patterns from operations data and enable the analysis of BigData. It can be used for accurate results with the integration of new and emerging technologies like IoT. 

With AI-baed mechanisms, Quality Assurance teams can trigger unattended test cycles, where defects are identified and remedial measures are triggered in run time, based on insights gained from historical data sets and past events.

An AI engine will ensure that only a robust code progresses from one stage to the next, orchestrating quality across the application development lifecycle. 


Benefits of Continuous Testing through AI:

  • An AI engine can promote the code or shut down features with a high probability of causing application outage or production defects depending on the data analytics and machine learning. 
  • Using the data patterns and correlations, machine learning algorithms can trace defects to root causes, with the AI triggering remedial tests before the code progresses. 
  • Machine Learning can leverage its algorithms to flag several coding errors that are previously overlooked and flags such as high memory usage, as a potential threat can be raised.
  • It ensures continuous testing through the best-fit tools, based on historical data and manages tools in advance based on a future requirement and unclogs the delivery pipeline. 
  • It helps organizations to shift from conventional tools to open-source tools, optimizing licensing or acquisition costs.


Conclusion:

Artificial Intelligence is a new magic tool that is transforming the app development market. organizations need to invest heavily in AI technologies and training. Though AI is an automated system, human testers are yet required to encode the AI with business process flows and critical scenarios. The knowledge of application development lifecycles is critical to executing such automated mechanisms. 

This can be developed into a market of itself by enterprises, who enabled infrastructures aligned with AI technologies and manpower trained for the same, by leasing out these AI engines and skilled manpower to other firms and teams looking to develop applications through automated mechanisms. 

Before, such a venture, enterprises must understand the landscape of the AI and IoT based technologies for app development with an evaluation of data logs and data richness of the enterprise archives that can facilitate effective data analytics. AI engines can be effective only if, the enterprise is able to maintain data from several processes or has high levels of automation that can provide relative data.

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The Internet of Things (IoT) or the connected ecosystem of devices, sensors, and computing systems is exploding with the latest technologies. As mobile devices are increasingly becoming more equipped with most advanced sensors and user-friendly user interfaces, they are playing a central role in the development and proliferation of the IoT ecosystem. No wonder IoT apps have emerged as the leading mobile app category with an era-defining impact on the lifestyle and development paradigms.

As the promise of this connected ecosystem, is not going to die down anytime soon, a famous mobile app development company working with IoT apps understand the opportunities promised by the connected ecosystem of gadgets and emerging technologies such as Machine Learning, edge computing, and in-memory computing.

Let's explain now the present state of things with iOS apps.

What do the Predictions and Statistics say?

According to most analysts of our time, the impact of IoT is really supposed to be huge as the vast majority of consumers are going to buy connected gadgets by the year 2019, as predicted by an Accenture group venture called Acquity. Another report by Gartner predicts that the total number of connected things across consumer homes, businesses, and industries will grow up to 26 billion by the time we reach 2020.

Improving Business Operation with IoT

With so much of promises on offer, naturally, organizations are trying to find out the best ways to equip their companies with the IoT ecosystem of gadgets and sensors. This obviously involves also combining the information fetched from a variety of connected sensors with predictive analytics. Modern enterprises are increasingly realizing the potential of IoT data when coupled up with analytics and the latest technologies such as Machine Learning. The smart apps utilizing the potential of IoT with the help of modern analytics and Machine Learning technology are actually trying to make things easier for their target users and customers.

Key Smart App Niches with Maximum Impact of IoT

While IoT is increasingly being integrated across industries and business niches, not all areas of IoT Integration are equally successful. Over the years, many people quickly refer to IoT as smart home gadgets, and it was the area where connected gadgets and apps started their journey.

Then comes the wearables like smartwatches and health and fitness bands that quickly became part of a smart gadget revolution. Then the connected car entertainment and navigation system became a massive reality with major thanks to the ridesharing apps like Uber and Lyft. Last but not least, the Industrial Internet of Things (IIOT) also became a reality with never-before promise for efficiency, productivity, and excellence.

Let us explain these key niches that gradually played the biggest role in the smart app revolution.

Smart Wearables

Smart wearables like smartwatches and fitness bands remain the most prominent category of smart mobile apps showcasing the value proposition of a connected ecosystem of devices. From a plethora of smartwatch brands with their own ecosystem of standalone wearable apps to the plethora of smart fitness and health tracker bands with their connected mobile apps, continue to contribute to the IoT ecosystem of smart applications.

Smart Connected Cars

The concept of smart connected car gas evolved over the years. While the basic smart connectivity with the car entertainment system to allow phone calls or using the virtual assistant to respond to emails are increasingly becoming part and parcel of automobile offerings from leading brands, the connected cars in the way of driverless car technology or remote navigation control system has still not become a marketable technology.

But as most car makers these days have their own mobile apps to allow users to exercise greater control while driving or boarding the car, connected car apps have become a big pushing factor for the automobile sector. The connected car apps are also evolving to help with various issues, and tasks ranging from real-time traffic feedback to monitoring the technical difficulties to alerts for maintenance needs to monitoring fuel consumption, etc.

Smart Home Apps

This is the oldest and most mature category of iOS apps that went through almost a whole evolution. Smart home gadgets ranging from the electric lights to the air conditioning systems to the connected refrigerators to the smart coffee maker, all gadgets that can be communicated and controlled using mobile apps, belong to this category. The smart home apps allow users to control their home gadgets with simple commands while enjoying the comfort and ease in lifestyle.

IIOT Apps

Industrial Internet of Things (IIOT) refers to the connected gadgets, devices, and sensors that, in an enterprise or industrial environment, help workers and employees to communicate and access data to complete tasks faster and with more efficiency. From the smart Beacon sensors or the geofencing technology in the retail stores to help to locate nearby customers to the use of connected security camera systems to process security information in real-time to the smart connected gadgets in the modern manufacturing units, there are a plethora of examples of Industrial Internet of Things (IIOT) applications.

Conclusion

As the IoT apps across all industries are rapidly proliferating and opening new and never-before opportunities of boosting efficiency and ease of use, should we not forget about the challenges to the IoT app development. The biggest challenge to the IoT mobile app development as of now concerns the data security and question of protecting privacy. In the years to come, with the ongoing excellence of IoT apps, addressing security challenges will continue to remain a key priority for the IoT app developers and strategists.

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IoT technologies or "Internet of Things" collect and analyze information about the object, its movement, condition, and many other features. In the European Union alone there are currently more than 13.3 millions of active trackers that use this system, which is a significant growth compared to 0.7 of a million in 2016.

An object of observation will be tagged for tracking with a relatively small device that collects the necessary information and sends it to you via Wi-Fi. But how one should know which type of IoT solutions to choose?

IoT Tracking Technologies

  1. RFID tags

RFID tags use radio frequency to identify the right element or track a certain "tag". In comes in two types:

  • Passive RFID tag depends on the RFID reader to send a wave that they can use to reply. For example, to see who passes through the reader bars in the store with an unpaid product.
  • Active RFID tags have an identifier along with a battery inside, which allows it to communicate with a reader on a larger distance.
  1. BLE beacons

BLE beacons rely on Bluetooth Low Energy so they can communicate, often used inside mobile phones. They can send multiple types of signals and detect many devices around them.

Beacons come in different forms and devices:

  • Parent beacons process and collect received data, communicate with child-beacons.
  • USB beacons
  • Router-sized beacons
  • Small portable beacons
  1. NFC chips

Near Field Communication is one of IoT technologies that rely on the electromagnetic field when are very close to each other (5-20 centimeters). NFC devices interact similar to RFID, can also be active and passive:

  • Active NFC sends and receives data (for example, it's being used on smartphones)
  • Passive NFC only sends information
  1. Zigbee hardware

Zigbee was invented for more complicated communication. They create a small network in a limited area, powered by a small radio.

Zigbee chips are widely used in radios and USB interfaces among other IoT solutions. It's also famous for its low cost and power expenses.

  1. LTE advanced

Long-Term Evolution is a wireless communication technology that was developed for faster internet, bigger storage and data processing. It's mostly used by mobile phones but sadly has different regions depending on the country where the phone was produced, with no support for a different frequency.

  1. LiFi

Visible Light Communication based Light Fidelity uses diodes to communicate at the speed of light without a chance for a human to notice the signal. The signal is then received by a photodetector.

LiFi is known to be the biggest rival of WiFi, though it's limited to the reach of the light that can be stopped by an obstacle.

  1. GPS

Everyone who owns a phone is familiar with Global Positioning System, which provides geolocation at a certain time to all GPS receiving devices. While still haven't beat by its accuracy in tracking, GPS is known to be quite power-consuming because it determines an object's location in non-stop mode.

  1. LPWAN

Low Power Wide Area Networks is created for long-distance communication and uses a low bit rate. It also allows to create a private wireless network.

Here some of the LPWAN based technologies:

  • NB-IoT uses a wide range in cellular services and devices
  • LoRaWAN uses a chirp spectrum radio module along with LPWAN technology
  • DASH7 is a firmware standard with low-latency, used over LPWAN

How IoT tracking helps in your business

Which of the IoT technologies is the best suited for your business?

Commercial Organization

  • A commercial organization may track their assets using RFID tags, such as Amazon keeps track of products in their vendor places
  • BLE beacons can help understand the customers, how much time they spend in the store, which aisles they visit and how they move across them
  • NFC technologies allow your customers to pay faster with their wireless credit cards
  • Zigbee is a necessity for those who develop smart home devices
  • LiFi help you set up shop displays and show advertisements to the customers

Industrial Business

  • BLE beacons help organize the inner industrial process, track equipment, monitor assets, prevent human errors and incidents
  • NFC takes care of security and access control
  • Zigbee helps with remote monitoring in a company with a large facility. However the cost rise drastically when operating between the facilities, so it's not used
  • LTE Advanced can instantly notify of a security breach and needed maintenance, write reports, draw a map of assets real-time movement
  • LPWAN optimizes costs and energy losses and power outrage. It monitors liquid levels, energy installations, optimizes solar plants performance

Healthcare Facility

  • RFID helps manage medical equipment and monitor the room's condition. It also helps with identification badges
  • BLE beacons help with indoor navigation
  • NFC tracks the patient's location, their time of treatment and health at home
  • Zigbee can monitor patients in real-time at low-cost
  • GPS tracks down the location of an emergency case
  • Li-Fi can lag when the light is interrupted. Otherwise, it's a perfect tool since it doesn't mess with another equipment
  • LTE has a personal network for enterprises. It's a large and secure network at a hospital

Logistics

  • RFID identifies a vehicle, person, baggage and therefore is helpful at railroad, airports, and roads
  • NFC helps scan tickets and trains passes fast
  • GPS helps to locate fleet vehicles and contact them
  • Modified with LED bulbs, LiFi cars help to prevent a collision in advance
  • Paired with other technologies, LTE Advanced can monitor the flight in real-time and communicate in long-distance
  • LPWAN can trace objects in real-time, optimize routes, detect and resolve faults, road threats, and maintenance

Agriculture and Food

  • RFID is helpful with tagging and locating cattle and food
  • GPS allows to plow and place crops precisely, map and monitor the field and save costs from farming
  • LPWAN is useful for measuring the soil moisture, water levels, cattle hygiene, and gate security

A wide range of IoT object tracking technologies is created to serve different purposes. Decide among the best of IoT solutions for yourself or read more in our blog to help determine which option is the best for you.

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IoT today is one of the most significant sources of new data. Considering that, data science will provide a considerable contribution to making IoT applications more intelligent and fast. Current applications of data science backed with Machine Learning has helped us deduce significant factors to help achieve optimum success in this field.

First, since data gets generated from different sources with specific data types, it is imperative to adopt or develop algorithms that has the capacity to handle the data characteristics.Next, the vast number of resources that generate data in real-time are not without the problem of scale and velocity. Conclusively, finding the best data model that fits the data is one of the most vital issues for pattern recognition and for better analysis of IoT data. 

These so called ‘issues’ have paved a path for a vast number of opportunities in expanding new developments. Big data can be laid down as high-volume, high-velocity, and high variety data that demands cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.

3 Major Concepts of Machine Learning in IoT

In order to better understand what algorithm best fits for processing and decision-making in the field of IoT, one needs to understand the most basic concepts of IoT.

  1. i) The overall application of IoT
  2. ii) The data-driven vision of ML algorithms

iii) Characteristics of IoT data

The overall application of IoT

As we know, the purpose of IoT is to develop a smarter environment and a simplified life-style by saving time, energy, and money. It also reduces significant amount of costs for major industries. Four major components of IoT include: 1) sensors, 2)processing networks, 3) data analysis data, and 4) system monitoring. Since IoT is integrated with a  number of technologies, and connectivity is a mandatory and sufficient condition for it to function, there are certain communication protocols which can are some of the most basic ingredients of this technology. Cumulatively, we need to enhance these components:

(1)Device to Device (D2D): is a type of communication which enables communication between nearby mobile phones; representing the next generation of cellular networks.

(2) Device to Server (D2S): is a type of communication device where all of the data is sent to the servers; can be either close or far from the devices. Such communication is majorly applied to cloud processing.

(3) Server to Server (S2S): is a type of communication where servers transmit data between each other and is majorly applied for cellular networks.


Before transferring data to other devices, one needs to prepare the data in order to establish communication. For this, there are various analytical processes and computing methods that are used.

Fog Computing:- This method is applied in order to migrate information from the data center task to the edge of the servers.

Edge computing:- The processing is run at a distance from the core in this type of computing.

Cloud computing:- Cloud has high latency and high load balancing, indicating that this architecture is not sufficient for processing IoT data because most processing should run at high speeds.

Once we understand the detailed classification and the purpose for which we intend to use the IoT device, we can establish the correct type of algorithm to use under the hood. Majorly this part of allocating algorithms comes up during the process of IoT app development and a lot of brainstorming goes behind it.

Let us have a look on the surface of some of the most widely-used and sophisticated Machine Learning algorithms that can be inculcated with the IoT devices.

A) Classification:- This type of ML algorithm is used in smart cities, especially for managing smart traffic. It helps in traffic prediction and in increasing data abbreviation.

B) Clustering:- This algorithm is used for smart traffic and smart health. It again aids in traffic prediction and in increasing data abbreviation along with patient data monitoring.

C) Linear Regression:- This algorithm is mainly used in economics and helps in real-time prediction along with data abbreviation.

D) K-Nearest Neighbours:- This algorithm is applied for smart-citizens and helps in analysing passenger travel patterns.

E) Feed Forward Neural Network:- Used for smart health purposes and helps in reducing energy-consumption and forecast the state of elements.

F) Canonical Correlation Analysis:- Used for monitoring public places and helps majorly in fault detection.

Conclusion

IoT has excited every single individual connected with information technology today. It promises an all-connected, all-encompassing future. These connections and smart devices together will lay down the foundation of a world we have so fondly visualized with sci-fi books and movies.

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The Arm AIoT Dev Summit is a developer-focused conference that provides a platform for you to exchange knowledge, discuss real-world use cases and solutions, and get hands-on with expert-led, deep-dive training and workshops.​ Along with like-minded developers, data scientists, and innovators, you will experience technologies enabling the Internet of Things (IoT), Artificial Intelligence (AI) and robotics.

Learn more and register here. Use discount code AIOTRICHARDNETWORK for an addiitonal $75 off!

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The automation of industry is steadily advancing into a new era – the fourth industrial revolution (4IR or Industry 4.0), where all things from machines and devices to people and systems will be digitally connected. Industry 4.0 technologies such as the internet of things (IoT), 5G, artificial intelligence (AI) and machine learning will enable industries to better manage their processes, improve efficiencies and boost their productivity. For many, the objectives for implementing 4IR technologies include greater control and predictability of production quality, improved safety and lower costs. Industry 4.0 also adds flexibility to an organization’s operations, enabling them to rapidly respond to shifts in consumer demand. To achieve these objectives cost-efficiently, however, requires taking a platform approach to digital transformation that is as much organizational as technological.

Industries that have been digitalized for decades, such as finance and online retail, treat IT and its infrastructure strategically — as crucial to their competitiveness. Amazon and Alibaba, the world’s two largest online retailers, for example, have invested hugely in their digital technology platforms. Ironically, Amazon’s AWS cloud business is currently its most profitable business, although it was originally only a platform for enabling its retail side. And these are not isolated examples of the importance of technology platforms in the digital era.

In industries where physical assets lie at the heart of operations, digitalization has been a slower and more complicated process. In these industries, Operational Technology (OT) organizations typically manage a wide range of production and logistics equipment — from manufacturing and assembly equipment to quality control and monitoring systems, to various hand-held devices/tools and material handling systems.

Legacy communications technologies and control protocols still prevail for these physical assets — with each supplier implementing their own customized versions of industry standards. That is why digital adoption has been slow; there are multiple layers of communication technologies and control protocols that create data siloes where exchanging of information between them is limited. This makes it difficult for operations to obtain a complete and accurate view of their production facilities.

As manufacturing and other industries are moving toward Industry 4.0, it’s becoming more apparent that this legacy communications architecture must change. Unfortunately, according to 451 Research, only 34% of industrial companies have a formal strategy to actively digitalize their business processes and assets — 10 percentage points less than non-industrial organizations. In order to fully move into an Industry 4.0 era, industrial-focused organizations are beginning to link OT with IT, embrace emerging technologies and build out digital platforms that can securely support new applications and use cases as they develop.

The building blocks of an Industry 4.0 platform include industrial IoT (IIoT), cloud, edge computing (MEC), AI and machine learning, digital twins and wireless communications — LTE/4G today, and 5G tomorrow.

IIoT systems connect all the physical assets with the digital platform. IIoT produces digital data that can be collected, integrated and analyzed across operations. Cloud computing enables organizations to quickly scale out resources for storing and processing the new, large volumes of data generated by IIoT. Edge computing, or edge clouds, distribute those parts of the processing that need to be closer to IIoT sensors and machinery for more rapid and precise response to sensor input; which is critical for automation. And as data security becomes an increasingly important part of operations, edge computing will enable critical processing data to remain within the facility premises, thereby protecting its integrity.

The sheer volume and complexity of IIoT data would be overwhelming without AI and machine learning (ML), which filter and process the data to look for actionable patterns. As a result, AI and ML create digital twins; essentially, digital models of the “virtual state” of a physical device, process or system. Leveraging the immense computing power of the cloud, digital twin technology enables these virtual representations to be used to provide predictive maintenance, conduct product or process simulations in order to optimize industrial processes before they are deployed, and in worker training to speed up competency. As a result, digital twins are the foundation component of Industry 4.0.

Given the key role that data plays in industrial automation, it’s clear why the communications network is vital as well. Unfortunately, however, the disparate communications technologies currently in use in many industries cannot provide the digital platform unification that’s required. This is where OT is learning from IT.

Because the platform has to be based on the current digital communications standard — IP — multiservice IP/MPLS networks are helping to accommodate the older communications technology use cases. Cabled networks, such as Ethernet, will still play a role, but linking hundreds of IIoT sensors, as well as mobile robots and vehicles, requires industrial-strength, next-generation wireless. And office wireless technologies, such as Wi-Fi, are not up to manufacturing performance requirements in terms of coverage, capacity, latency or security. As a result, digitally transforming organizations moving toward Industry 4.0 are leveraging IP-based LTE/4G to cover the vast majority of today’s requirements. Moving forward, 5G, with its improved performance beyond LTE, will be able to support many new use cases and applications as Industry 4.0 adoption accelerates.

For those organizations that are already investing in IIoT and cloud platforms, the importance of their communications network to enable industrial automation and the digital transformation of their facilities can’t overlook or under-estimated. To ensure that no site, employee, or system is left behind, organizations in industrial-focused fields must also think strategically about their communications platform.

Over the last few decades, productivity growth for some industrial sectors has lagged behind others where digital technologies have been widely adopted. One of the key lessons that asset-intensive industries can learn from these more progressive “digital” businesses is in the power of digital platforms to remain competitive in a fast-changing world.

 

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Application development is one of the most challenging processes for enterprises and choosing a model approach for the same is a complex decision to make. An application development model or Software Development Lifecycle Model(SDLC) is the heart of any development process. There are several models for SDLC like agile, waterfall, V-shape, iterative, spiral, etc.

The battle of agile and waterfall for the dominance over SDLC model acceptance has been a happy hunting ground for developers around the world. Developers and enterprises are looking forward to tapping into agile methods to create applications faster, secure and leaner. But, there are ardent followers of the waterfall model that are still using it as an SDLC model for application development.

What is the waterfall model?

The waterfall model is based on a waterfall-like structure of phases of any application development lifecycle. Each phase has an iterative relationship with each other that provides direct value to the end-product. Other phases are needed to be staffed and planned differently for the best utilization of program resources.

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Image Source: SDLC Models Explained

There is a sequel dependability among the phases, which holds back the system design whenever the analysis model is still to be signed off and holds back coding if design is still to be signed off. Each development step progresses, and the design is further detailed by iteration with every preceding and succeeding step.

Due to the addition of the preliminary program design phase between requirements and analysis phase, the designer assures that the software or app will not fail because of storage, time or data flux. The waterfall model relies on documentation of every phase, with a view of building a shorter and smarter phase consisting of all the phases to ensure customer involvement in both during and after the program design phase.

What is the Agile model?

Agile techniques depend on the iterative development and a focus on iteration, communication and the reduction of resource-intensive intermediate artifacts. It combines short iterative cycles with the feature planning and dynamic prioritization. Any agility in development of apps or softwares require face-to-face interactions that can be achieved through close customer relationships.

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Image Source: SDLC Models Explained

These customer relationships can help teams make decisions immediately rather than waiting for the correspondence to happen from the customer's side. Each iteration in agile methodology is an iterative product itself. They are like self-contained mini-projects with activities that span requirement analysis, design, deployment, and test.

These iterations encapsulates all the digital resources across the teams and act as a subset of the final system. The customer provides feedback based on the observations of current iterative releases and specify requirements for further iterative releases. 

Enterprises hire ios developers and android developers to exploit the iterative releases across platforms prevalent in agile model. The predetermined length of an iteration serves as the deadlines for the teams.

In this SDLC model, each iteration is better known as a "Sprint". The sprint is a 30-day development iteration, where the whole process of an iterative release is carried out in 30 days. During the sprint, there is no change to be made in the metrics and parameters of a sprint and the same should be reviewed by the teams at the end of the sprint. 

A wholistic comparison between Agile and Waterfall methods:

 

  1. Primary Requirements: For conventional methods like a waterfall, the major set of objectives are predictability, repeatability, and optimization. While Agile techniques focus on rapid value and rapid response to the changes.

 

  1. Scaling: Waterfall techniques are better for scaling large projects. While agile methodology is not good at scaling large projects and suits best for the smaller projects where the organizational structures of a waterfall system fails.

 

  1. Customer Relations: Agile methods works better when it comes to customer relations with a condition that customers operate in a dedicated mode with the development teams. This method risks the pitfalls of implicit knowledge, which is solved through documentation in the waterfall model. 

 

  1. Planning and control: The waterfall model focuses on project management requirements like careful planning, estimation, coordination, tracking, and control. While agile methods are more focused on the results than documentation.

 

  1. Communication: Agile techniques advocate face-to-face communications and waterfall methods require explicit documented knowledge.

 

  1. Requirements of Process: The agile model does not entertain the up-front and formal requirements engineering. While the waterfall model encounters problems with rapidly changing requirements.

 

  1. Development: The waterfall model relies heavily on the infrastructure of a software or application as a part of the development sequence. While the agile model values the working software or app over documentation and emphasizes simplicity. 

 

  1. Testing: The waterfall model focuses on architecture and documentation adopting conventional assurance methods that involve dynamic testing, static analysis with internal and third-party evaluation. The agile model facilitates internal design and code review that encourages developers to adopt the coding standards.

 

  1. Skill Of Customers: Agile requires dedicates, co-located and knowledgeable customers. While the waterfall model needs adequately skilled and knowledgeable customers.

 

  1. Developers: Waterfall developers are to be plan-oriented, adequately skilled with the knowledge of external skills. While agile model needs developers that are knowledgeable, co-located and collaborative with amicable communicative and interactive talents. Agile approaches emphasize the cross-functional teams of developers, testers, subject matter experts and architects of application infrastructures. 

 

Conclusion:

A plan-driven waterfall model or an adaptive agile method are both advantageous and disadvantageous in several ways. If an enterprise has a large project at hand, the waterfall model is the best suited SDLC and if there is a small project at hand than the agile model is best suited. But. when it comes to medium-sized projects, both the models struggle in terms of handling and execution over medium-sized projects.

With rising costs and time constraints on development projects, the agile model can create apps more rapidly owing to its sprint tool which is a very short iterative method. While the waterfall model has large costing issues with staffing and tools required for several phases in the interactive relationships and with the focus on external testing, it incurs heavy costs on the project budget. So from the above, it is clear to choose the most suitable model according to your project requirements.

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To all members at IoT Central:

My team at Arm is delivering a brand new developer conference called the AIoT Dev Summit this December, 2 - 3. The conference will be held at the Computer History Museum in Mountain View and there will be multiple hands-on workshops with industry leaders in AI, IoT and robotics, plus keynotes and tech talks.

You can see the full agenda here: http://bit.ly/2WHOVqh

I think this is a special event, and I would like to extend my personal discount code to all IoT Central members. Tickets are currently $175 and for an additional $75 off use: AIOTRICHARDNETWORK

Please check it out and thank you!

Richard


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$13 trillion in ROI will be generated by 2025 - BI Intelligence.

Over 20 billion devices will be connected to the IoT by 2020 - Gartner

These predictions about IoT clearly reflects how rapidly this futuristic technology is evolving. To stay ahead of the curve, diverse industry-specific businesses are already investing heavily in different IoT initiatives. No wonder why IoT has become the “talk of the town” in the digital world. 

In this article, you are going to get a detailed insight on IoT - perks of adopting IoT in businesses, which industries are benefiting the most from it, how IoT is transforming the mobile app development sector along with what we can expect from this futuristic technology in 2020 and beyond.

IoT advantages for businesses 

By 2020, the IoT platform is expected to grow at a Compound Annual Growth Rate (CAGR) of 40%. So, what’s the secret behind its global popularity?

Well, through customized IoT mobile solutions, this advanced technology helps in addressing some common business challenges including

 

  • Safe data access
  • Safe data storage
  • Device control and management
  • Integration and maintenance

 

Allowing the real-time data exchange to carry out different business actions and analysis is one of the major reasons why businesses are going gaga over it. The list of IoT’s wide range of business benefits includes

 

  • Enhanced productivity

 

When it comes to the point of dealing with real-time data and variables, IoT does it the best. IoT-based applications help in management procedures. Also, it can help in carrying out automation of routine-based functions, informing employees about expected technical disruptions along with supporting remote troubleshooting procedures.

 

  • Better customer experience

 

With IoT-based applications, businesses can offer a seamless and smart customer experience. Users can carry out transactions using smart trackers, mobile card readers, etc. Also, the smart meters and smart grid technologies help users to identify and resolve issues. 

IoT-based devices are capable of collecting a plethora of data on users’ behavior which helps businesses to come up with innovative ways to keep their customers engaged and offer better customer experience.

 

  • Cost-effectiveness

 

Both the IoT devices and the IoT-based applications assist professionals not only to monitor equipment but also to diminish the downtime along with the risk factors. The applications based on this advanced technology can successfully predict possible system misalignments and failures which in turn helps in saving a lot for businesses.

Thus, IoT has become one of the most loved technologies to implement these days. 

Industries to benefit from IoT applications

As IoT technologies help in reducing overall business operating costs, increasing business visibility, business efficiency and productivity along with creating additional revenue streams, businesses across diverse industries are embracing it wholeheartedly. 

Healthcare and fitness

Today’s market is flooded with different IoT-enabled wearables. Such smart wearables help in monitoring calorie intake, heart rate, steps taken while walking, sleep along with tracking various other activities that help us to stay fit and healthy. 

Other than personal use of health wearables, some smart appliances like thermometers, scales, blood pressure monitors, etc. are presently available in the market. 

Smart home

The idea of home automation was relatively unfamiliar to most people until recently. With the emerging IoT technology, smart home automation has started to show its true power. Smart homes make our lives easier, more convenient, and more comfortable. 

Increased energy efficiency, better home security, savings on the electricity bill, maximized comfort, etc. are some popular reasons why smart home automation development with IoT is trending in the market these days. 

Retail and Supply Chain Management

Well, if you think different IoT devices and applications in the Retail industry is limited to only shopping and SCM, you are wrong. Enabling IoT in business is an opportunity for hospitality service providers, restaurants, and other businesses to manage not only their supplies but also to gather valuable insights. 

It allows business owners to avert order overflow, effectively restricting the employees who abuse their privileges along with managing the merchandising and logistical expenses in a better way. Business owners now can manage their inventory in real-time with IoT. 

Automotive

Self-driven cars or connected cars are no longer fiction only. Thanks to IoT. Thus, in the automotive industry, IoT use cases are actively expanding. Smart applications are being developed and integrated into car infotainment systems so that providing telematics, in-car navigation, and entertainment becomes easier than ever.

Also, IoT-enabled apps make sure predictive maintenance, surveillance, security, and safety of the vehicle along with real-time monitoring, cognitive insights for the management, etc. 

Other than the above-mentioned ones, industries related to manufacturing, agriculture, logistics are also ripping benefits out of IoT. 

IoT in mobile app development - what to expect next? 

You have already seen how IoT is transforming the way different industries operate. According to experts, IoT adoption is still in the early phase. The way the connected world of IoT is evolving, soon we can experience its power to the fullest. Even worldwide app developers would agree that IoT is leaving significant impacts on iPhone and iPad app development services. So, what can we expect from this futuristic technology in the future?

Edge computing will become more popular than cloud computing

We all know how cloud computing brought a wave in the digital world. Even today’s IoT devices store all the data in their cloud. However, in the tech world, change is the only constant. And this is why we will probably soon witness edge computing becoming more popular than cloud computing. 

Now, the question is how?

Instead of sending all the data from devices to the cloud, now, the IoT devices will transfer data to a local storage device first. This device can filter, sort, and accordingly can calculate the data and transfer only the required data set to the cloud. 

Undoubtedly, it will reduce traffic to the network. Also, collecting and processing data locally will allow the IoT apps to consume less bandwidth and work in bad connectivity to the cloud. 

IoT security will get more priority

The graph for IoT application adoption in businesses is increasing exponentially. Now, with more devices being connected to the network, not only the data volume increase but the risk for data security increases as well. 

We have seen how the smart home industry and health care industry is adopting various IoT-based applications. So, be it patient’s health-related data or data related to the home security, everything is being stored in the cloud. So, with sensitive data floating in the cloud, we can expect IoT security will get more priority in the next year and beyond. 

A unified framework for integration

To keep the industry safe and secure, a unified framework is required. The lack of a unified IoT framework - this is a serious challenge that IoT has faced while cooperating with different industries. However, another trending technology Blockchain will be a great help to accelerate the IoT adoption process by allowing the app developers to improve and develop mobile and web applications. 

So if someone is looking to develop IoT apps and looking for an Android or iOS app development company, it is important to know beforehand if they are capable and know the integration. 

IoT and AI

Both Artificial Intelligence and IoT are data-driven technologies. And both technologies are used for storing and analyzing data. So, to make automation more efficient, we may see these two thriving technologies being implemented together to gain better visibility along with accurate insights into various services. 

Other than what we mentioned above,

  • We will see the rise of predictive maintenance
  • Businesses will deliver more personalized customer experiences
  • Software-as-a-Service will be the new normal

And all of these will be the direct or indirect impact of IoT being implemented in the mobile apps. 

However, mobile app developers have to advance their skill sets to integrate IoT successfully in their apps. Having sheer knowledge of Swift or Xcode won’t be enough for smart iPhone or iPad app development services. 

Of course, we will witness new technologies being emerged. However, these will make IoT easier to use and more intuitive to a large extent. 

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To outsource or not to outsource?

 

Depending on who you are talking to, the idea of outsourcing can promote some very positive or negative reactions. ‘Off-shoring’ and ‘unfair competition’ are thrown against ‘specialization’ and        ‘lower costs’. Whether you are considering product development, the provision of specialist services or the handling of back office activities, there are a number of pros and cons that need to be considered.

What is outsourcing?

Outsourcing is defined as ‘the process of paying to have part of a company's work done by another company’. It can therefore cover a wide range of business activities and is usually undertaken as a cost-cutting or efficiency optimization measure. Investopedia states that was first recognized as a business strategy in 1989 and became an integral part of business economics throughout the 1990s and makes the point that ‘the practice of outsourcing is subject to considerable controversy in many countries. Those opposed argue it has caused the loss of domestic jobs, particularly in the manufacturing sector. Supporters say it creates an incentive for businesses and companies to allocate resources where they are most effective, and that outsourcing helps maintain the nature of free market economies on a global scale’.

Typically then, a firm will have a project or an ongoing activity that it wishes or needs to undertake but which, for example, it does not have the necessary in-house skills to undertake, does not form part of its core activities, or which it does not have the resources to fully undertake. The firm will search for another company that specializes in the area and seek to outsource the particular activities to them. The IT sector is one of the main areas – along with Human Resource and finance – that thrives on outsourcing.

Benefits of outsourcing

There are a number of advantages of outsourcing:

  1. Greater access to expertise. By working with firms who are specialists in a particular area, a company can gain greater access to the relevant skills and knowledge in a quicker timeframe. This can include access to cutting-edge tools and concepts and insight into the developments within the sector that would otherwise not be available. Using an outsourced firm can also give access to a wider pool of expertise and talent, as the contractor will have access to these within its own sector – access that the contracting firm would not be able to gain.
  2. Greater efficiency. One of the key tenants of economic efficiency, going back to Adam Smith and the Wealth of Nations in the 1770s, is that specialization can increase efficiency and that greater efficiency can increase economic returns – that is, at a company level, by specializing on its core activities, a company is better able to gain a competitive advantage and increase financial returns. By thus avoiding diverting resources into non-core activities and relying on specialized outsource companies to provide these non-core activities (which are core for the contractor company), greater productivity can be generated.
  3. Reduced costs. One of the primary benefits of outsourcing to hire a dedicated team is that the contracting firm does not need to employ more people to undertake temporary or non-core activities. Given that staff costs make up a large component of ongoing expense for a company, this can substantially reduce costs. As a factor, this should not be underestimated: in the EU, for example, firms need to add an extra 24% in non-wage costs (from 6% in Malta to 33% in France).
  4. Developing partnerships. Outsourcing can help a company develop relationship with partner companies, whether domestically or abroad. This in turn can generate further business opportunities.

The downsides to outsourcing

There are, however, some disadvantages to outsourcing:

  1. Lack of direct control. While the relationship between the outsourcing firm and the contractor will be determined by a contract or by a service level agreement, there is a level of reduced control that comes from outsourcing.
  2. Changes in requirements. Business requirements change, this is a fact of life. But if you need to change the contracting agreement between a company and the contractor, this can be difficult to do if – for example – you are in the middle of a several year-long agreement, or it can result in increased costs for the change in service to be accepted.
  3. Increased communication issues. Contracting out some of your activities or product development can result in increased communication problems, with staff in both companies having to understand two different companies’ ways of communicating. This can lead to misunderstandings and, in some cases, cause serious problems if there is not the goodwill to resolve issues.
  4. While product development, for instance, with a specialist contractor can result in a world class product, by definition in an outsourcing relationship you are in the hands of the contractor, to a degree. This means that if the quality of the product is not that which you wanted or which you had agreed with a stakeholder, you will often not be able to solve it yourself and will need to work with the contractor to do so – and that will often involve addition costs.

Summary

The decision on whether to outsource, for example for product development or to hire a dedicated development team is one that each company needs to assess for itself. There are considerable advantages in terms of gaining access to expertise and skills and keeping costs controlled. But at the same time there are potential risks of which a company needs to be aware. With effective management and good communication, these risks can be substantially reduced – but both sides in the relationship need to be aware of the need for this and take steps to ensure that the outsourcing runs effectively.  

 

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The term Digital Transformation means different things for different people. Some people might think of it as switching from manual processes to autonomous processes, while for others it might be about the insights that the data brings, which can help in making business decisions. What can Digital Transformation or moving towards Industry 4.0 do for the manufacturing sector? It can lead to enhanced production cycles, increased customization, a focus on reinforced products and better access to information for employees.

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Blockchain and IoT: are they a perfect match?

As IoT becomes more prevalent, more CIOs are asked to take the reins of IoT projects. Gartner recently found that just under a third of responding organizations expected their CIO would lead their IoT efforts, and that by 2020, more than 10% of IoT projects in traditional industries would be headed by the CIO.

This prompted Jenny Beresford, research director, to caution: ‘The IoT will expand rapidly and extensively, continually surfacing novel and unforeseen opportunities and threats.’

Among those threats — which will definitely be CIOs’ responsibility — is the woeful security of traditional IoT and IIoT networks, as well as the privacy, connectivity and transaction speed issues that frequently plague IoT implementation.

To be maximally effective such a network must somehow be both highly connected and highly secure, and currently only one technology — blockchain — can achieve this.

However, obstacles remain, including the lack of an IoT-friendly blockchain consensus protocol.

Network Security and Data Exchange

IoT and IIoT networks typically lack physical security, host-based defences, and software updates and patches. These networks typically also use less-secure wifi protocols, web apps and APIs, combining larger-than-usual attack surface with weaker-than-usual security while retaining single points of control and failure.

In IoT, hackers see a new prize: gigantic botnets which can be used to spread malware, as with the Mirai botnet. And in IIoT, the rewards of network penetration can be industrial sabotage, espionage or large-scale blackmail, like Florida’s Riviera Beach.

Yet, companies cannot afford to hold off indefinitely on deploying IoT technology, since doing so exposes the organization to risk of being outmanoeuvred by competitors. Blockchain offers CIOs a way to deliver their IoT projects with the inherent security issues of large, distributed networks essentially solved.

Blockchain for IoT inherently eliminates single points of control and failure while simultaneously offering modular encryption and auditable transaction logs, so security issues are isolated, easy to identify and cannot spread through the network. Even if they do, they can’t gain control of it.

Transaction Processing

Machine-to-machine (M2M) communications generate gigantic amounts of data in transit — and the number of connected devices is growing rapidly:

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With centralized control, much of the processing power of these devices is lost to idling, while trust issues keep transaction costs high. CIOs find themselves in the position of paying for computational capacity they can’t use, and for traditional data centers that represent a ‘honeypot’ for attackers and a bottleneck for their networks.

Peer-to-peer communication across connected devices would enable dynamic transaction load balancing, enabling spare computing power to be identified and employed and potentially eliminating centralized data storage.

To do this successfully, IoT will need to become trustless as well as peer-to-peer. Blockchain offers a trustless peer-to-peer communication and transaction medium with secure, unforgeable and auditable transaction logs; smart contracts can be used to set policies, control and monitor access rights and execute actions autonomously based on pre-defined conditions.

Privacy and Autonomy

IoT systems built on traditional networks cannot prevent access by governments, service providers or criminal actors. With weak security and single points of control, trust on these networks is impossible to guarantee.

IoT and IIoT both require connectivity and modular security. The current solution, ‘security through obscurity,’ must be replaced by a systemic shift to open-source systems that achieve ‘security through transparency’ and are far less vulnerable to sophisticated, persistent institutional attacks.

Without this shift, both consumer and industrial networks will be increasingly vulnerable, and as the number of connected devices grows, radically lower-cost privacy and autonomy will be necessary to save the IoT.

IoT Connectivity Costs

In the current iteration of the IoT, costs are prohibitively high while revenues fail to meet expectations. Many existing IoT solutions are expensive because of the high infrastructure and maintenance costs associated with centralized cloud delivery and large server farms.

IoT devices violate the traditional pricing and revenue model of the IT industry too: device costs and incomes don’t line up, and maintenance costs consume substantial amounts of revenue. Inherent technical reasons make this unavoidable using the current model, but CEOs still don’t like hearing it from their CIOs.

Cost reduction

Blockchain technology allows reliable data to be pooled and shared without trust, directly among stakeholders. This allows for a significant cost reduction, eliminating intermediaries and allowing for automatic transactions and payments across devices using smart contracts.

Blockchain-IoT Integration Challenges: Lack of an IoT-centric consensus protocol

The current consensus protocols available for blockchains — PoW, PoS, PoET, and IOTA — are all designed for permissionless blockchains focusing on financial value transfer. PoS and PoET can also be used in permissioned blockchains, but their consensus is probabilistic and does not end in a permanently-committed block, resulting in an unacceptably high ‘hard fork’ rate.

PoET requires specialist hardware and the enclave allocating wait time is a trusted entity; it has also proven vulnerable to node compromise.

What’s needed is a consensus that can keep the benefits of the distributed, auditable, trustless environment blockchain provides, but deliver it in real time and at scale — without mining or excessing transaction costs, and without multiple hard forks.

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Embedded systems are maybe the most complex part of an integrated IoT solution. Looking at my company's experience I can say that most programmers that come to build IoT systems have to have additional experience if they want to work with hardware. Customers that want to hire IoT developers also need to have a basic understanding of what skills his future contractors must have.
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