Subscribe to our Newsletter | To Post On IoT Central, Click here


Platforms (131)

Today, retail stores are constantly focusing on leveraging the emerging technologies like cloud, mobile, RFID, beacons, etc., to provide connected retail services and better shopping experience to customers. For example, store owners are integrating sensors in the key zones of retail stores and connecting them to cloud through a gateway that enables real-time data analysis related to products, sales, and customers from these sensors.

Interestingly, IoT and connected technologies are taking the retail industry by storm. 96% retailers are ready to make changes required to implement the Internet of Things in their stores

IoT in retail can help retailers improve store operations, enhance customer experience and drive more conversions. Moreover, IoT can help retailers solve day-to-day problems such as tracking energy utilization, managing in-floor navigation, detecting crowded areas, reducing check out timings, managing product shelves, preventing theft, monitoring goods, etc. Let us how IoT helps in few of these scenarios.

 

 

In-Store Navigation with IoT-enabled Devices

Identifying in-store navigation is one of the common problems in retail stores. Here, IoT devices with integrated technologies like Bluetooth, Wi-Fi, magnetic positions and augmented reality, etc., can facilitate in-store navigation to help customers navigate through the store and find the desired product.

It gives customers a multichannel shopping experience through digitization of physical assets. In-store navigation also helps increase the path to purchase rate before a product stock outs.

Example:
Bluetooth low energy (BLE) beacons are small sensors placed strategically throughout the retail store. These sensors are equipped with Bluetooth smart technology and compatible with smartphones. This BLE beacon device sends out continuous radio signals to nearby smart devices in the range. Smart devices in that range catch the signal and trigger events such as availability of a new product or launch of a new offer. Further, that device sends a unique ID to cloud server. The server checks that ID and responds back, through which communication between signal and smart device is established using a unique ID. Almost all customers nowadays carry smart devices like mobile phones and tablets. If BLE is used, customers can be notified on their smartphone with personalized coupons and deals as soon as they enter the store.

The above solution improves customer’s in-store experience and also increases footfall ratio. It also facilitates quick product search and increases conversion rates while generating a powerful shopping environment that can help enhance product offerings and store layouts.

Energy Management with Smart Devices

Energy consumption is a major cost consuming factor for the retail businesses, be it in refrigeration, lighting, heating, air conditioning, etc. Using these energy sources efficiently can bring cost saving of up to 20 percent per year. IoT-enabled smart devices can help resolve problems of energy management and saving.

There are several IoT-based platforms that can log, monitor and beep alarms or alert the in-store personnel about temperature, energy usage, heating, gas leakage, electricity breakdowns, etc., with the help of integrated sensors. Using these smart energy management devices, store owners can directly interact with the controllers of refrigerators and retrieve prioritized information with the help of sensors.

Example:
Every year, a large retail chain attributes nearly $2B of loss to wasted or spoiled food, with issues relating to its legacy refrigeration system, accounting for approximately 15% of this total—or $300 mm. In case of emergency situations like powercut or excessive heating, alarms from the controllers of these refrigeration systems reach the operations team only after 5 or 6 hours, and there is no mechanism to provide warnings before these situations occur. Here smart refrigeration IoT device can provide cloud-based temperature monitoring solution to notify the controllers about emergencies using temperature sensors and mesh networking technology.

Theft Prevention with Geo-Fencing

The crime of shoplifting in the retail industry is increasing day-by-day, because retailers fail to provide sufficient attention to shoplifters. According to National Association for Shoplifting Prevention (NASP), more than $25 million worth of merchandise gets stolen from retail shops each day. Adding more to retailers’ loss is retail shrinkage, which includes shoplifting, employe theft, paperwork error, vendor fraud and many more.

To overcome the problem of shoplifting and retail shrinkage, retailers can use Geo-fencing technique.
Geo-fencing relies on the global positioning system or a radio frequency identification (RFID) tag that allows a store operator to create a virtual barrier or zone around specific locations in retail shops. When a customer tries to move product from the specific location, an alert is triggered and a message is sent to the store in-charge. Geo-fencing enabled in IoT devices or beacons can help retailers in a number of ways; from keeping goods safe, tracking customers and employee movements, managing company-owned resources to minimizing incidents of theft and loss.

Customer Engagement with Sensor-Enabled Shopping Carts

The sensor-enabled shopping cart is a technique adopted by most of the retail merchandisers. These shopping carts help retailers grow their business in every aspect by helping them visualize shopper’s flows by category/subcategory, understand the shopping pattern, analyze the dwell path, and enable faster checkout.

This smart cart design involves sensors with connectivity protocols around the cart, which have the ability to track the movement of the wheels and match up with the distance the cart has traveled. It helps retailers with an accurate data of shopping carts with the inside-store journey. The data from this cart can be sent to the server or to cloud for further analysis.

Read more…

With the exponential increase in the IoT and connected devices, it is difficult to ensure scalability, security, and robustness of these devices. Cloud computing platforms like AWS help enterprises accelerate their development to deployment cycles, enhancing robustness and scalability of the entire IoT solution.

People perceive cloud as a platform only for storage and computing. However, there are many other capabilities that cloud offers with cloud computing, such as application deployment, data transfer, database management, etc. Moreover, with the onset of IoT and connected technologies, the role of cloud computing has expanded even more in terms of enabling communication between devices and providing scalability to applications.

How Cloud Computing Helps in IoT Deployment

In today’s time, deploying an IoT solution takes a lot of effort and time, due to the increased number of software applications and hardware integration it requires. Also, when it comes to deploying a new, robust and scalable IoT platform for any industry vertical, it can be very tedious and costly to set up the infrastructure. For example, in a smart factory model, there are many machines and devices to be connected to the cloud. Developing a whole new infrastructure for those Internet of Things applications from the scratch can take up to five to six months’ time in development, deployment, and testing. This prolonged time delay is not appropriate since enterprises need to respond to the market demands quickly, especially when the market competition is too high and when the connected devices and technologies are increasing exponentially. This is where cloud computing plays a crucial role in IoT deployment.

There are several cloud platforms and service providers such as AWS (Amazon Web Services), Azure, and Google Cloud for deploying IoT solutions. Of these, we will focus on the integrating AWS cloud platform in this blog.

Why AWS Cloud Platform

Cloud service platforms like AWS help enterprises accelerate their development cycle from months to a few days and hours, allowing them to build a robust and scalable IoT solution. AWS platform also allows easy and secure on-boarding of billions of devices according to the enterprise’s needs. It is one of the robust platforms for accelerated development, which enables the developers to connect the device to cloud quickly. AWS has recently launched AWS IoT 1-Click that easily triggers the Lambda function for any device to perform a specific action.

AWS is offering various services like cloud computing, machine learning, analytics, storage, IoT platform, security, AR & VR, etc. With AWS, organizations are just paying for the services that they utilize, which provides the benefits of cost reduction and better asset management.

Let us see how an enterprise IoT solution can be leveraged with the AWS IoT platform.

Sensor and Device Connectivity with Edge Analytics

The most important and basic aspect of an IoT solution is to connect all the devices and sensors to the cloud for management and control. Since the development of software and services to connect the devices to the cloud is tedious and time-consuming, AWS IoT Core helps IoT developers with AWS IoT SDK, which allows them to choose SDKs according to their choice of hardware for applications development. These applications help users in managing their IoT devices on air.

  • The AWS IoT SDK supports C, JavaScript, Arduino, Python, iOS, and Android with open source libraries and developer guide, which helps developers with their IoT product development. AWS IoT Core consists of the Device Gateway that allows bidirectional communication between devices and the AWS. The device gateway ensures that the devices are communicating through cloud securely and efficiently in real time. This device gateway supports MQTT, Websockets, and HTTP 1.1. It can also support billions of devices at a time without the infrastructure management.
  • Device gateway also consists of the AWS Greengrass a software agent that runs the computing on the edge for the connected devices. Greengrass consists of the Lambda Function, which allows users to run the rule engines, which are coded for particular events like temperature rise, light intensity, etc. AWS Greengrass also brings the AWS to the devices so that they can perform the local compute on the data when they are already using the cloud for other processes like management and storage. It can also be programmed for transferring only necessary information to the cloud after the local compute has been executed.
  • Greengrass enables the device to cloud data security by encrypting the data. This data can be secured for both local and cloud communications. So, no one can access this data without any authentication. It uses the same security model as AWS IoT Core, which contains the mutual device authentication and authorization and secured cloud connectivity.
  • Organizations can also create the digital twins, also known as Device Shadowing, for their IoT devices in the AWS cloud. In device shadowing, the current state of IoT devices gets replicated in the cloud virtually and this virtual image can be accessed at the time of no internet. This helps in the prediction of the desired future state of a device. IoT Core then compares this desired state with the previously accounted state and can send the command to the device for making up this difference.

Cloud Computing and Storage

The Internet of Things generates a huge data at every moment. The storage and management of this data require a lot of infrastructure deployments and maintenance efforts. AWS provides storage and computing services, which help enterprises in reducing the infrastructure development cost. These services also provide real-time analytics and accessibility of the data at any moment. Also, the developers can access the required data from the cloud without any delay.

  • When we talk about the data management, AWS Kinesis can be considered as a great example of the real-time data streaming and analytics. It continuously analyzes, captures, and stores the huge heterogeneous data (terabytes per hour) that gets generated from the IoT devices or any other resources.
  • After the data has been stored, Amazon EC2 (Elastic Compute Cloud) provides a secure, resizable, compute capacity in the cloud. Its web service interface allows developers to scale their computing requirement with minimal efforts. Users can scale up and down their computing resources according to the requirement and they just have to pay for the resources utilized. Apart from that, AWS also provides data storage services as AWS S3 and Glacier. They both provide 99% durability, comprehensive security and compliance capabilities that can help meet even the most stringent regulatory requirements. Amazon S3 and Glacier both allow running powerful analytics on the data on the rest.
  • For Database management, AWS provides its service called AWS DynamoDB as NoSQL database that can support both key document-based database. Due to the NoSQL database, it enables benefits like ease of development, scalable performance, high availability, and resilience.
  • For data and asset security, AWS has features and services like AWS Identity and Access Management, AWS Key Management Services, and AWS Shield along with the AWS Cloud HSM to enhance the security.

eInfochips (an Arrow company) is an Advanced Consulting Partner for AWS services. We help clients in implementing a highly scalable, reliable, and cost-efficient infrastructure with custom solutions for IoT on the AWS platform. Know more about our AWS services.

 

Read more…
IoT Tech Expo was unique in that provided opportunities to connect with leaders at the intersection of internet-of-things(IoT), artificial intelligence(AI) and blockchain.  Speakers showcased discussed their projects and many vendors shared their expertise.  Presentations and panelists discussed real-world implementations from John Deere, Porsche, Pfizer, Harley Davidson just to name a few.  The conference itself covered a lot of ground: there were entire speaker tracks for IoT Developers, Connected Industry, Connected Transportation, AI Analytics for IoT, AI in the Enterprise, Blockchain for the Enterprise, Blockchain for Enterprise, Cryptofinance & ICO Strategies, Blockchain for Business, and Blockchain development. This article shares some the key take-aways and interesting anecdotes from IoT implementations we collected from the show.
Read more…

The Dynamics of ODMs and OEMs

I've seen a lot of different thoughts about "original equipment manufacturers" and "original design manufacturers" recently, so I figured I'd offer my observations from my time working in Shenzhen for my IoT company.

Backstory: we’re partnered with Qualcomm to cloud enable bluetooth mesh technology across myriad US, Asian, and European based companies, primarily for lighting and smart home products in consumer/commercial markets. I spent about 6 months in Shenzhen and Hong Kong during 2017 putting together the supply chain partnerships.

From what I’ve experienced, “brand,” i.e. the companies we’re familiar with as consumers, and Original Equipment Manufacturer “OEM” are used interchangeably, while Original Design Manufacturer “ODM” refers to the “factory.”

In most of my interactions, there is a tight albeit painful relationship between the OEM and ODM in consumer electronics because cooperation between multiple vendors is often required to get a product to market, especially in IoT. Typically, the most differentiated intellectual property (IP) is in the hands of the OEM (brand)— industrial design, software, firmware, and it’s in their best interests to obfuscate as much as possible throughout the supply chain to make it harder to replicate the technology, which everyone assumes will happen. And it does. This is especially true during the rise of the IoT, where connectivity challenges plague both sides of the pond, and clever solutions are the 11th hour superpower everyone is fighting to find first to use as leverage in the supply chain. 

There is another class of manufacturers— not sure the technical name, but we call them “module makers” — companies that specialize in the design and production of drop-in PCB modules for various connectivity chipsets to make them easier to productize. An example would be ITON, who provides chips for several of GE’s products to the prime ODM (such as Leedarson or Eastfield) who is responsible for final assembly (note: many ODMs are also module makers— they keep chips in house to maximize control and profits).

Both ODMs and module makers participate in a process of product innovation that presupposes the market. Chipmakers (and other tech vendors) like Qualcomm send their reps out to the factories to demo new silicon technology in the form of a “reference design” in a bid to get the ODM to create a module or product based on that chipset that answers to a trend they’ve noticed from their OEM/brand customers. In this way, the ODM bears the R&D cost as a bet for business, but doing so gives them a chance to retain the right to get a royalty on every module sold. Ask an ODM to hand over any firmware they've made and they’ll tell you with their sweet puppy dog eyes “eat my shorts” because it’s how they keep you from just taking everything to another vendor.

For brands like Home Depot (or more generally companies less interested in designing hardware) these ODMs are essential because they are flexible enough to develop a catalog of partially developed products on speculation— whatever successfully sells up the food chain at Home Depot, they make real (note: the “make real” part is where a lot hits the fan because this stuff is hard to scale).

The OEM-ODM-module maker ecosystem creates a sort of “it takes a village to make a product” atmosphere, but with grumpy uncles, annoying neighbors, and meddling kids abounding. There's a constant sense of quiet espionage on both sides, although that tends to get better if you develop a direct relationship with your mfg partners. Western business has evolved to sustain trust with purely transactional relationships-- this is way less true in places like China. Go to lunch with them and take them to dinner a few times, invite them to Macau, get them drunk and having fun with you. These relationships are insurance policies on getting screwed. Further, having boots on the ground near your manufacturing is practically a requirement nowadays if you want to have any hope of your supply chain operating smoothly. 

In the case of a brand like Apple, who meticulously defines and controls every little detail of their product and supply chain works with an Electronic Manufacturing Services company “EMS” like Foxconn who primarily invest only in building other designs precisely to specification.

So OEM v. EMS: OEM: “build this for me, exactly like this, and don’t ask too many questions, or I’ll eat your children.” 

EMS: ;)

The ODM/OEM relationship is a bit shakier: 

OEM: “build this for me, and pretty please do your best not to use lead paint or explode my users.” 

ODM: ¯\_(ツ)_/¯

All that said, many companies I’ve encountered are chimeric— companies that usually do business as an EMS could also be caught as an ODM if the opportunity is right. I’ve wracked my brain over how to approach meetings with ODMs that also have an OEM/brand side to the company. The ODM side is a potential partner while the OEM side is a potential customer— in the already confusing world of IoT this can be quite the rollercoaster.

I could be off, but the cash value of the above has navigated me through hella lots of conversations from ivory tower to where the dog food gets made. It is a truly global and complex web of associations, across cultural, language, political, and social boundaries. Read “Poorly Made in China” and “Barbarians at the Gate” to see the differences in East vs. West strategies for business success, which I see as orthogonal values of Replication and Dominance.

If you’re interested, here’s a great article by a Shenzhen based supply chain expert: https://www.linkedin.com/pulse/3-types-partners-product-managers-can-use-development-changtsong-lin/

 

Thanks for reading! Our company is expert at IoT integrations, and we thrive on building ecosystems of partners with positive feedback loops on new services and revenue streams. Kindred spririts, please reach out to me at [email protected] 

 

Best, 

 Preston

COO @ Droplit

https://droplit.io

[email protected]

 

Read more…
A field guide describing the 5 approaches to industrial IoT platform development and how to know which approach is the right one for your enterprise based on your goals, requirements, constraints, and where you are today in your digital transformation journey.
Read more…

IoT Evolution or IoT Revolution

During all these years evangelizing on the Internet of Things (IoT), I have been explaining to customers, partners and friends that IoT can positively change the way we do business and the way we live our lives.  I have been asked if IoT is a new revolution in our society, or it is just one more step in the technological evolution of the he digital revolution. Today, the debate continues but whether evolution or revolution, The Internet of Things is here to stay.

If you have read AIG´s whitepaper entitled “Internet of Things: Evolution or Revolution?” you learned IoT, from its origins, to its applications in business, the risks associated with its inevitable arrival and how with the IoT is coming bringing dramatic changes. In the whitepaper we discover that in spite IoT is often presented as a revolution that is changing the face of society or the industry in a profound manner. It is an evolution that has its origins in technologies and functionalities developed by visionary automation suppliers more than 15 years ago

I definitely think it’s an evolution

The development of the Internet of Things is a bold move. IoT is not just a leap from the Internet. The Internet of Things brings with it an evolutionary force that we rarely see in technology.

It is important not scare the most conservative enterprises. It is not about ripping out current automation systems to replace them with new technologies. End users will resist rapid and radical change because of the increased risk of downtime and associated costs.

I think that this debate should be framed in a more general question. What Age period are we living?

 

The Connected Age or the Age of Sensorization

I consider the start of the Connected Age when the Internet of Things term was coined by Kevin Ashton executive director of the Auto-ID Center as the title of a presentation he made at Procter & Gamble (P&G) in 1999. Probably Kevin envisioned that the move to sensorization will transform every industry in the world.  In the Age of Sensorization, it’s possible to make more accurate and quantifiable assessments using real time sensor based information.

The main driving force behind the Connected Age is data – data that can be collected, data that can be analysed, data can be shared and data can be used to improve many service offerings.

Data is the new oil in this AgeThe global sensorization is driving new ideas and thoughts that will ultimately drive innovation in our personal, business and working lives. Sensor´s data is opening up new opportunities, driving new business models and taking innovation to new levelsNo doubt that sensors’ data is a valuable commodity. The European Commission has proposed to impose a tax on the revenue of digital companies based on their users’ location, on the grounds that “a significant part of the value of a business is created where the users are based and data is collected and processed.”

We are still living in the Connected Age. I expect this Age ends in 2025, no because there will not be more things to connect but because is when most of things will become intelligent and start controlled by robotsThe Robotic Age or the Age of Artificial Intelligence

Reading Genesis of AI: The First Hype Cycle, I  rediscovered how Artificial Intelligence (AI) was born and evotution till now. But it was after I read Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It? I realised maybe I was wrong and we already living the final years of the Connected Age and we are entering before 2025 , not without a certain fear, the Robotic Age.

According to IDC: ”By 2019, 40% of digital transformation initiatives – and 100% of IoT initiatives – will be supported by AI capabilities.

Qualcomm envision a world where edge AI makes devices, machines, automobiles, and things much more intelligent, simplifying and enriching our daily lives.

AI has emerged as the most exciting capability in today’s technology landscape. It’s potential is rich in large, complex organizations that generate massive amounts of data that can be fed into AI systems.

Data is the crucial ingredient of the AI revolution. We can envision that  AI -driven companies will represent the future of broader parts of the economy and  we may be headed for a world where labor’s share falls dramatically from its current roughly 70 percent to something closer to 20 to 30. At the same time the number of robots will increase and be part of the society.

Robotics and Artificial Intelligence have reached a crucial point in their evolution. A robot is no longer just a mechanical device capable of interacting with its environment and carrying out an assigned task. At present, the main research laboratories all over the world are developing and implementing in sophisticated robots technical, practical and even philosophical tools. Nevertheless, we can not forget that there are still problems in the land of AI.

Could we avoid psychopath and sociopath robots?

Companies need to move quickly to embrace AI so that they can support the burgeoning Internet of Things (IoT) and deliver the kinds of services customers are demanding.

Finally, if your company is thinking about Build or Buy Artificial Intelligence, take a look at this article.

The Cognitive Age

The cognitive revolution was a period during the 1950s-1960s when cognitive psychology replaced Behaviourism and Psychoanalysis as the main approach in psychological fields. Increasing focus was placed on observable behaviours in conjunction with brain activity and structureFor those of you who believe the mind the centre of all things, David Brooks, the New York Times columnist, wrote two editorials  that point to wider transformations that are shaping the world in which we liveWe could consider the start of Cognitive Age when Facebook abandoned an experiment after two artificially intelligent programs appeared to be chatting to each other in a strange language only they understood. The two chatbots came to create their own changes to English that made it easier for them to work – but which remained mysterious to the human.

Are we sure Facebook shut down Its Artificial Intelligence Program?  Facebook not the only company or government running secrete AI programs. Are you scaredThere are many myths about Cognitive. This article pusblished by Deloitte the Consulting company help dispel five of the most persistent myths.

  • Myth 1: Cognitive is all about automation
  • Myth 2: Cognitive kills jobs
  • Myth 3: The financial benefits are still remote
  • Myth 4: AI is overhyped and bound to disappoint
  • Myth 5: Cognitive technology is just for ‘moonshots’

We need to start thinking how to  prepare ourselves and our business for the Cognitive Age.” As I explain in “Bring Your Own Cyber Human (BYOCH) – Part 1: Augmented humans” we are in the path to being cyber humans. To live in the Cognitive Age, I encourage companies to invest in how to enhance our senses and to increase our intelligence to compete and win over robots.

Key Takeaways

The Connected Age is a fact. ARM is predicting 1 trillion IoT devices will be built until 2035.  For those who think that the IoT is a revolution, not be worried because we are just simply in an evolutionary process.

With the introduction of AI and machine learning, enterprises will be able to embark on projects never thought possible before. The Robotics Age is going to be a great challenge for humanity. The fear of being inferior to our creation, not being able to control them, to compete with machines for a job, to have to obey them will really mean the beginning of a revolution.

What does AI mean for the future?. What will be the implications and the risks? Will AI really understand humans?. With the current skills humanity will be in inferiority to face the cognitive systems that will populate Cognitive Age.  That is why I encourage governments, private laboratories and researchers to work on  Augmented Humans projects if we do not want to be slaves to our uncontrolled inventions.

Thanks for your Likes and Comments.

Read more…

 

What is a smart city? The answer depends on who you ask. Solutions providers will tell you it’s smart parking, smart lighting or anything to do with technology. City officials may tell you it’s about conducting city business online, such as searching records or applying for permits. City residents may tell you it’s the ease of getting around, or about crime reduction. Everyone is right. A smart city, built properly, will have different value for different stakeholders. They may not think of their city as a “smart”city. They know it only as a place they want to live in, work in, and be a part of. To build this type of city, you have to first build the smart city ecosystem.

 

A smart city is built on technology, but focused on outcomes

A scan of the various smart city definitions found that technology is a common element. For example, TechTarget defines a smart city as “a municipality that uses information and communication technologies to increase operational efficiency, share information with the public and improve both the quality of government services and citizen welfare”. The Institute of Electrical and Electronics Engineers (IEEE) envisions a smart city as one that brings together technology, government and society to enable the following characteristics: a smart economy, smart mobility, a smart environment, smart people, smart living, smart governance.

But what does a smart city really do? Our scan of smart city projects worldwide showed that initiatives fell into one or more smart city “outcomes” (Figure One).

Figure One. Smart city projects are aligned to one of seven outcomes.

 

As a starting point, we define a smart city is one that uses technology extensively to achieve key outcomes for its various stakeholders, including residents, businesses, municipal organizations and visitors.

 

The smart city ecosystem framework

Figure Two shows our framework for a smart city ecosystem. A vibrant and sustainable city is an ecosystem comprised of people, organizations and businesses, policies, laws and processes integrated together to create the desired outcomes shown in Figure One. This city is adaptive, responsive and always relevant to all those who live, work in and visit the city. A smart city integrates technology to accelerate, facilitate, and transform this ecosystem.

Figure Two. The smart city ecosystem framework.

 

Four types of value creators

There are four types of value creators in the smart city ecosystem. They create and consume value around one of the outcomes listed in Figure One.

When people think of a smart city, they automatically think of services provided by municipal and quasi-government agencies, such as smart parking, smart water management, smart lighting, and so on. In fact, there are three other value providers and users that co-exist in the smart city – businesses and organizations, communities, and residents.

Businesses and organizations may create services that use and create information to create outcomes for its stakeholders. Some examples of “smart” businesses include Uber and Lyft for personal mobility, NextDoor for information sharing, and Waze/Google for traffic and commute planning.

Communities are miniature smart cities, but with very localized needs. Some examples of potential smart communities include university campuses, office parks, airports, cargo ports, multi-dwelling unit (MDU) or apartment complexes, housing developments/neighborhoods, business districts and even individual “smart” buildings. They have needs for smart services that may be tailored specifically for their stakeholders.

Residents or individual citizens are also smart services providers in the smart city. A resident living near a dangerous street intersection can point a camera at the intersection and stream that information live to traffic planners and police. Residents place air quality measurement sensors on their properties to monitor pollution and pollen levels during certain times of the year, and make that information available to other community members. Residents can choose to make these smart services temporary or permanent, and free or fee based.

 

The Smart City is built on layers

A smart city is an ecosystem comprised of multiple “capability layers”. While technology is a critical enabler, it is just one of many foundational capabilities that every smart city must have. No one capability is more important than the rest. Each capabilities plays a different role in the smart city. These capabilities must integrate and coordinate with each other to carry out its mission.

 

Value layer. This is the most visible layer for city residents, businesses, visitors, workers, students, tourists and others. This layer is the catalog of smart city services or “use cases”, centered around the outcomes (Figure One), and offered by value creators and consumed by the city stakeholders.

Innovation layer. To stay relevant, value creators in the smart city must continuously innovate and update its services for its stakeholders. Smart cities proactively facilitate this through a variety of innovation programs, including labs, innovation zones, training, ideation workshops, skills development and partnerships with universities and businesses.

Governance, management and operations layer. The smart city creates disruption and results in digital transformation of existing processes and services. Smart city management models must integrate a new ecosystem of value creators and innovators. They must plan, support and monetize new business models, processes and services. They must upgrade their existing infrastructure and management processes to support “smart” services. Finally, they must measure the performance of the city with a new set of metrics.

Policy, processes, and public-private partnerships, and financing layer. The smart city doesn’t just magically appear one day. An entirely new set of engagement models, rules, financing sources, and partners are required to build, operate and maintain the smart city. Cities must develop a new set of “smart” competencies in order to get and stay in the “smart city game”.

Information and data layer. The lifeblood of the smart city is information. The smart city must facilitate this in several ways, including open data initiatives, data marketplaces, analytics services, and monetization policies. Equally important, they must have programs that encourage data sharing and privacy policies to protect what and how data is gathered.

Connectivity, accessibility and security layer. People, things and systems are interconnected in the smart city. The ability to seamlessly connect all three, manage and verify who and what is connected and shared, while protecting the information and users is crucial. The highest priorities for smart cities are to provide a seamless layer of trusted connections.

Smart city technology infrastructure layer. Most people automatically think of technology when talking about smart cities. The smart city technology infrastructure must scale beyond the traditional municipal users and support a new class of value creators, and city/user stakeholders.

 

Leveraging the smart city ecosystem framework

The smart city is a complex ecosystem of people, processes, policies, technology and other enablers working together to deliver a set of outcomes. The smart city is not “owned” exclusively by the city. Other value creators are also involved, sometimes working in collaboration and sometimes by themselves. Successful and sustainable smart cities take a programmatic approach to engage its stakeholders across the ecosystem.

Our research has found that many cities are not taking an ecosystem approach to smart city projects. This is due in part to smart city projects being managed by the Information Technology (IT) organization where their charter is on systems development and deployment. In contrast, more experienced smart cities manage their smart city programs through internal cross functional “Transformation” or “Innovation” organizations.

Regardless of where cities are in their smart city journey, they must get ahead of the “curve” with smart city projects. They begin by thinking in terms of building the broader ecosystem in order to create a sustainable and scalable smart city. Key next steps include:

  1. Understand the smart city ecosystem framework and tailor it to the realities of their specific city. Incorporate this model into the development of their smart city vision, strategy and execution plans.
  2. Relative to the smart city ecosystem framework, identify current capabilities and gaps across the various layers. Understand what is needed to support the four types of value creators.
  3. Evaluate existing and new smart city projects and initiatives against the ecosystem framework. Use this framework to identify what is missing from the project plans and what is needed to make the projects fully successful.
  4. Prioritize and develop competencies across the various ecosystem layers. A smart city requires new skills and competencies. Augment existing capabilities through strategic partnerships and contracting with service providers, as required.

 

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

This post was co-authored with Renil Paramel, an IoT Innovation Catalyst, Strategist and Senior Partner at Strategy of Things.

Read more…

The Internet of Things is network connectivity between physical devices such as appliances, vehicles, etc. which contain inbuilt sensors, software, and microchips that facilitate data transfer between each other. Each device has its own unique computing processor which allows them to interoperate with other similar infrastructure via the internet. Things are always changing, we must accept the ebb and flow of things. The real question you should ask yourself is where you should concentrate your efforts in the next few years to avoid alienation. Our concerns over the past few years have changed drastically, in terms of the things we build and design and how the users interact with these devices.

The Shape of Future: The applications of the Internet of Things are extensive. The number of devices with the capability to link up with each other via the internet went up by 31% in 2017. Experts predict by 2020 the Internet of Things will have a total value of $1.7 trillion in the global market and a total of 30 billion new devices will be designed with network connectivity features.

Human intervention will reduce in the years to comes, some careers might become obsolete in a few years for example taxi and delivery packages, translators and interpreters, pilots and air traffic controllers and many more. IoT allows devices inclusive of all the computing enabled infrastructure can be remotely controlled therefore integrating the physical world with the computer system resulting in more economic benefits, efficiency, and accuracy.

How to Secure Future: To secure your Internet of Things career there are several things you could do. First, start by learning a few programming languages, most recommended JavaScript. This will not only secure your career but also gives it longevity. The language is not only used on browsers but increasingly, with Node.js, it’s a language for the servers, which is more often than not found directly embedded within devices.

Ensure you are always updated in terms of internet security. Constantly refine your security skills on how to maximize security on an ever-increasing number of connected devices. Try and run tests to ensure the security measures put in place can hold up when required.

The ability to come up with small accurate sensors e.g. sensors that can detect a change in temperature, speed, and other physical elements will be an invaluable skill in the future as far as the internet of things is concerned. Some sound knowledge of simple things such as Wi-Fi, Bluetooth, and transfer of data to the cloud will go a long way in safeguarding your career.

Don’t be daunted: Don’t stop what you are doing because humans will always need to interact with devices and machines to make them work. Rather than looking at Internet of Things as means of reducing jobs, look at it as a channel that could create even more job opportunities. Don’t be daunted, after all, you have come this far and along the way you have developed some useful skills. With a little effort, your Internet of Things career will thrive.

Read more…

What are going to be new things in IoT 2018?

The Internet of Things (IoT) wasted no time spreading across the world and connecting a huge number of individuals. Apart from, we have seen almost every major industry put lots of resources into IoT, and foremost industries are rapidly moving to implement IoT solutions that drive the primary concern. Despite the huge gains in connectivity, the truth is, 2018 will be more of a steady growth period for the IoT. Using IoT, successful organizations will create a self-learning environment. 

These five innovations will be the top IoT trends in 2018 and could be an essence of the world yet to come.

IoT future shaped by wearables

While 1 out of every 3 smartphone users trusts they will have at least 5 wearables by 2020. So, high demand towards wearable devices such as smartwatch, health & fitness band etc. In this manner, a setback in wearable adoption may delay the overall adoption of the IoT among consumers.

Roll out voice-based services to consumers

Google Assistant, Google Virtual Assistant that lives on devices like smart speakers and gaining enormous fame. An ever-increasing number of devices will open marketers’ eyes to better approaches for interacting with customers. Industries like financial and some other businesses that request authentication for much else, besides a simple task, will slack. The complexity, broadness and quality of voice-based services will grow in 2018 with accessible services.

Security: Blockchain

Security is still the weak link in the internet of things, so security remains a prime challenge for IoT. Blockchain will play a vital role in improving security for financial transactions in 2018. Watson IoT Blockchain enables devices to participate in Blockchain transactions as a trusted party. IoT and Blockchain empower more transactions overall because they eliminate centralization.

Big Data, Machine learning and AI

The amount of processed data will grow, and due to more number of smart devices, we will use IoT much more than we do now. So, we should work with Big Data in order to consider assets that would empower us to process and analyse problems accurately. Here, Machine Learning is the most demonstrated AI innovation that can process data based on predictive analytics, without the need of manual programming and activate real-time tasks in the IoT channel.

Connected devices will double

In 2018, Internet of Things will have considerably more interconnected devices, like a digital nervous system with interfacing devices together and be exchanging data. It is not only laptops and mobile phones also there will be more smart devices that we use daily, like smart doors, smart jar, smart locks, smart fork and more. The number of connected devices grew exponentially from 4.9 million in 2015 to 6.1 billion in 2016. It is expected to 46 billion by 2021. 

 

Read more…

Cloud computing allows companies to store and manage data over cloud platforms, providing scalability in the delivery of applications and software as a service. Cloud computing also allows data transfer and storage through the internet or with a direct link that enables uninterrupted data transfer between devices, applications, and cloud.

Role of Cloud Computing in IoT:

We know that the Internet of Things (sensors, machines, and devices) generate a huge amount of data per second. Cloud computing helps in the storage and analysis of this data so that enterprise can get the maximum benefit of an IoT infrastructure. IoT solution should connect and allow communication between things, people, and process, and cloud computing plays a very important role in this collaboration to create a high visibility. 

IoT is just not restricted to functions of systems connectivity, data gathering, storage, and analytics alone. It helps in modernizing the operations by connecting the legacy and smart devices, machines to the internet, and reducing the barriers between IT and OT teams with a unified view of the systems and data. With cloud computing, organizations do not have to deploy extensive hardware, configure and manage networks & infrastructure in IoT deployments. Cloud computing also enables enterprises to scale up the infrastructure, depending on their needs, without setting up an additional hardware and infrastructure. This not only helps speed up the development process, but can also cut down on development costs. Enterprises won’t have to spend money to purchase and provision servers and other infrastructure since they only pay for the consumed resources. 

(Case Study: DevOps for AWS, Continuous Testing and Monitoring for an IoT Smart City Solution)

How Cloud Services Benefit an IoT Ecosystem:

There are several cloud services and platforms that play different roles in the IoT ecosystem. Some of the platforms also come with inbuilt capabilities like machine learning, business intelligence tools, and SQL query engines to perform complex analytics. Let us understand how these cloud services and platforms benefit an IoT ecosystem.

Cloud Platform for Device Lifecycle Management:

Enterprises create applications and software through cloud services (SaaS), which can connect devices and enable device registration, on-boarding, remote device updates, and remote device diagnosis in minimal time with a reduction in the operational and support costs. Cloud introduces DevOps within the IoT ecosystem, which helps organizations automate many processes remotely. As more and more devices get connected, the challenges with data security, control, and management become critical. Cloud services enable IoT remote device lifecycle management that plays a key role in enabling a 360-degree data view of the device infrastructure. Certain cloud providers offer multiple IoT device lifecycle tools that can ease the update and setup of firmware and software over the air (FOTA).

Application Enablement Cloud Platform:

Cloud enables application development with portability and interoperability, across the network of different cloud setups. In other words, these are the intercloud benefits that businesses can take advantage of. Intercloud solutions possess SDKs (Software development Kits) on which enterprises can create their application and software without worrying about the backend processes.

Enterprises can run and update applications remotely, for example, Cisco is providing the application enablement platform for application hosting, update, and deployment through the cloud. Enterprises can move their applications between cloud and fog nodes to host the applications and analyze & monitor the data near the critical systems.

Many cloud service providers are focusing on building the cloud environment on the basis of OCF standards so that it can interoperate smoothly with the majority of applications, appliances, and platforms, that will allow D-to-D (device-to-device) M-to-M (machine-to-machine) communicationOpen Connectivity Foundation (OCF) standardization makes sure that the devices can securely connect and communicate in any cloud environment, which brings in the interoperability to the connected world.

Digital Twins:

Device shadowing or digital twins is another benefit that an enterprise can avail through cloud services. Developers can create a backup of the running applications and devices in the cloud to make the whole IoT system highly available for faults and failure events. Moreover, they can access these applications and device statistics when the system is offline. Organizations can also easily set up the virtual servers, launch a database, and create applications and software to help run their IoT solution.

Types of Cloud Computing Models for IoT Solutions

There are three types of cloud computing models for different types of connected environment that are being commonly offered by cloud service providers. Let’s have a look:

Cloud Computing Models

 

Infrastructure as a Service
  • It offers virtual servers and storage to the enterprises. Basically, it enables the access to the networking components like computers, data storage, network connections, load balancers, and bandwidth.
  • Increasing critical data within the organization lead to the security vulnerabilities and IaaS can help in distributing the critical data at different locations virtually (or can be physical) for improving the security.
Platform as a Service
  • It allows companies to create software and applications from the tools and libraries provided by the cloud service providers.
  • It removes the basic needs of managing hardware and operating systems and allows enterprises to focus more on the deployment and management of the software or applications.
  • It reduces the worry of maintaining the operating system, capacity planning, and any other heavy loads required for running an application.
Software as a Service
  • It provides a complete software or application that is run and maintained only by the cloud service provider.
  • Users just have to worry about the use of the product, they don’t have to bother about the underlying process of development and maintenance. Best examples of SaaS applications are social media platforms and email services.

 

Apart from these, cloud service providers are now offering IoT as a Service (IoTaaS) that has been reducing the hardware and software development efforts in IoT deployment.

Example of implementing cloud computing set-up in a connected-factory:

There are different sensors installed at various locations of an industrial plant, which are continuously gathering the data from machines and devices. This data is important to be analyzed in real time with proper analytics tools so that the faults and failures can be resolved in minimal time, which is the core purpose of an industrial IoT ecosystem. Cloud computing helps by storing all the data from thousands of sensors (IoT) and applying the needed rule engines and analytics algorithms to provide the expected outcomes of those data points.

Now, the query is which cloud computing model is good for industrial plants? The answer cannot be specific, as every cloud computing model has its own applications according to the computing requirement.

Leading Cloud Services for IoT Deployments

Many enterprises prefer to have their own cloud platform, within the premises, for security and faster data access, but this might not be a cost-effective way as there are many cloud service providers who are providing the cloud services on demands, and enterprises just have to pay for the services which they use.

At present, Amazon Web Services (AWS) and Microsoft Azure are the leading cloud service providers. Let’s see the type of cloud platforms and services AWS and Microsoft Azure provide for IoT implementations

AWS IoT Services

AWS has come up with specific IoT services such as AWS Greengrass, AWS lambda, AWS Kinesis, AWS IoT Core, and a few other cloud computing services, which can help in IoT developments.

AWS IoT Core is a managed cloud platform that allows devices to connect easily and securely with cloud and other devices. It can connect to billions of devices, store their data, and transmit messages to edge devices, securely.

AWS Greengrass is the best example of an edge analytics setup. It enables local compute, messaging, data caching, sync, and ML inference capabilities for connected devices in a secure way. Greengrass ensures quick response of IoT devices during local events, which reduces the cost of transmitting IoT data to the cloud.

AWS Kinesis enables data streaming that can continuously capture the data in terabytes per hour.

AWS Lambda is a compute service that lets you run code without provisioning or managing servers. It executes code only when required and scales automatically from a few requests per day to thousands per second.

AWS DynamoDB is a fast, reliable, and flexible NoSQL database service that allows enterprises to have millisecond latency in data processing, enabling quick response from applications. It can scale up automatically due to its throughput capacity, which makes it perfect for gaming, mobile, ad tech, IoT, and many other applications.

AWS Shield is a managed Distributed Denial of Service (DDoS) protection service that safeguards applications running on AWS. It provides automatic inline mitigation and always-on detection that minimize the application downtime and latency. This is why there is no need to engage AWS Support to benefit from DDoS protection. There are two tiers of AWS Shield — Standard and Advanced.

Microsoft Azure IoT Services:

Microsoft has come up with many initiatives in the field of IoT, providing industrial automation solutions, predictive maintenance, and remote device monitoring, etc. It is also providing services like Azure service bus, IoT hub, blob storage, stream analytics, and many more.

Azure Stream Analytics provides real-time analytics on the data generated from the IoT devices with the help of the Azure IoT Hub and Azure IoT Suite. Azure stream analytics is a part of the Azure IoT Edge that allows developers to analyze the data in real-time and closer to devices, to unleash the full value of the device generated data.

Azure IoT Hub establishes bidirectional communication between billions of IoT devices and cloud. It analyzes the device-to-cloud data to understand the state of the device and takes actions accordingly. In cloud-to-device messages, it reliably sends commands and notifications to connected devices and tracks message delivery with acknowledgment receipts. It authenticates devices with individual identities and credentials that help in maintaining the integrity of the system.

Azure Service Bus is a great example of cloud messaging as a service (MaaS). It enables on-premises communication between devices and cloud in the offline conditions also. It establishes a reliable and secure connection to the cloud, and ability to see and monitor activities. Apart from this, it protects applications from temporary spikes of traffic and distributes messages to multiple independent back-end-systems.

Azure Security Centre is a unified security management and threat protection service. It monitors security across on-premises and cloud workload, blocks malicious activities, advanced analytics system to detect threats and attacks, and also can fix vulnerabilities before any damages.

AWS and Microsoft Azure are providing a robust IoT solution to enterprises. An IoT Gateway can collaborate with multiple cloud service providers to maximize the advantages of the cloud solutions for IoT systems.

Read more…

The White Knight of IoT Platforms

In spite the Internet of Things term was coined by Kevin Ashton executive director of the Auto-ID Center as the title of a presentation he made at Procter & Gamble (P&G) in 1999, it was only when companies like Pachube (an early leader in the burgeoning “Internet of things” field) launched a web service  that enabled to store, share & discover real time sensor, energy and environment data from objects & devices around the world, when most of us believed that the time to IoT was finally had arrived.

 

Since its founding in 2008, Pachube pretended to be the leading open development platform for the Internet of Things.  In 2011 when the company was acquired by Woburn, Massachusetts-based LogMeIn in a deal that was worth "approximately $15 million in cash that re-branded the service as Cosm, but it was still a “beta” test version, to finally launch Xively that become a division of LogMeIn.  LogMeIn did not want or did not know how to incorporate the potential of Xively into its business. And in 2017 again Xively lost its charm.

Google the White Knight of Xively

On February 15, we wake up with the new that Google will acquire IoT platform Xively from LogMeIn for $50 million, according to Bloomberg, to expand in market for connected devices. Google has been the White Knight of Xively.

 

Another White Knights

In December 30, 2013 - PTC announced it had acquired ThingWorx, a PTC Technology for approximately $112 million, plus a possible earn-out of up to $18 million. The acquisition of ThingWorx positioned PTC as a major player in the emerging Internet of Things era. Later, in July 2014 PTC acquired Axeda Corporation for approximately $170 million in cash which Gartner estimated is an acquisition multiple of just over 6 times revenue.

In February 2016, Cisco Acquired Jasper Technologies for $1.4 Billion in cash. How wonderful White Knight.

A software goliath company like SAP acquires a small IoT startup like PLAT.ONE  now part of SAP?

In 2016, Microsoft did not disclose the sum for Italian start-up Solair acquisition. Th startup  expanded Azure capabilities.

In March 2015, Amazon was taking another step into the Internet of Things acquiring 2lemetry, a startup with a system for sending, receiving, and analyzing data from Internet-connected devices.  2lemetry had raised at least $9 million. Investors included Salesforce Ventures.   

 

We all know that the IoT Platform market need a quick consolidation

The M2M/IOT Platform market has changed in the last 10 years. The fragmentation is unsustainable and I can say that I do not see a clear IoT platform market leader yet that works as a plug-and-play fix for all kind of connected-device creators. Besides, the rush of investors for IoT platform companies trigger rumors of new acquisitions increasing significantly their actual valuation and encourages thousands of entrepreneurs and startups to create new IoT platform copies of each other. Although there is still room for new innovative IoT platform startups, the decision to trust in a company able to simplify the complexities of the IoT, with a scalable and robust infrastructure and drive real results for your business, will reduce the choice among a short list. The bad news is that the hundreds of IoT platforms startups must compete now with the platforms offered by Tech and Industrial Giant vendors.

 

Given the confusion that exists about the IoT platforms, companies need to approach experts’ advisors that will recommend which platform(s) is most suitable for your current and future business and technical requirements.

 

There will not be White Knights for everyone

In “Be careful of the Walking Dead of IoT, I alerted that in spite that no one has the crystal ball, it is almost sure that many IoT platforms are not going to continue within 10 years, not even within 1, 2 or 3 years in this inflated market. As show in the picture below, some Tech Giants have been looking and found some of the best pieces. What will happen to the 700+ platforms out there? There will not be White Knights for everyone. At least for Xively it has been a happy end.

Thanks in advance for your Likes and Shares

Thoughts ? Comments ?   

 

Read more…

Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. 

While IoT may be seen as another buzzword at the moment, companies like SAP, Cloud Sigma, Net Atlantic and Amazon Web Services are working to make sure that for businesses, IoT is a reality. It’s companies with this willingness to change, adopt and invent that will win the new economy. Mobile phones, online shopping, social networks, electronic communication, GPS and instrumented machinery all produce torrents of data as a by-product of their ordinary operations. Most companies want their platform to be the foundation of everything it does, whether it is with big data, data analytics, IoT or app development. The same  rub off phenomenon was emulated in Latin American countries  like Brazil, Argentina, Mexico and European countries like Brussels, Italy,  Germany, Denmark , Poland and Prague in recent times.

It is important to realize that technology is exploding before our very eyes, generating unprecedented opportunities. With easy access to cheap cloud services, smarter people came up with these platforms, and it has fundamentally changed businesses and created new ways of working. Mobile cannot be an afterthought. It needs to be integrated in everything you do and positioned at the forefront of your strategy. You have no valid reason to avoid migrating to the cloud. Cloud provides a ubiquitous, on-demand, broad network with elastic resource pooling. It’s a self-configurable, cost-effective computing and measured service. On the application side, cloud computing helps in adopting new capabilities, meeting the costs to deploy, employing viable software, and maintaining and training people on enterprise software. If enterprises want to keep pace, they need to emulate the architectures, processes and practices of these exemplary cloud providers.

One of the main factors of contributing value additions is the concept of a Smart City which is described as one that uses digital technologies or information and communication technologies to enhance the quality and performance of urban services, to reduce costs and resource consumption and to engage more effectively and actively with its citizens. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other.The idea is to embed the advances in technology and data collection which are making the Internet of Things (IoT) a reality into the infrastructures of the environments where we live. We will interact and get information from these smart systems using our smartphones, watches and other wearables, and crucially, the machines will also speak to each other. Technologists and analysts are on a path to discovery, obtaining answers on how technology and the data collected can make our cities more efficient and cost effective. The current model adopted for IoT is to attract businesses to develop software and hardware applications in this domain. The model also encourages businesses to put their creativity to use for the greater good, making cities safer, smarter and more sustainable.

A few years ago like many others  I predicted  that Business models will be shaped by analytics, data and the cloud. Moreover, the IoT is deeply tied in with data, analytics and cloud to enable them and to improve solutions. The key goal is to ensure there is value to both customers and businesses. You can effectively put this strategy into action and build a modern data ecosystem that will transform your data into actionable insights.  

Till we meet next time...

Best,

Raj Kosaraju

CIO 

 

Read more…

 

The Internet of Things (IoT) enables vendors to create an entirely new line of “smart” solutions for its existing and new markets. While the decision to go “smart” is straightforward, the decision of how to do so is not. Vendors are faced with a “build, buy, partner” decision – build it themselves, buy or license it from someone, or partner with a complementary solution provider and go to market together. This article discusses some of the key considerations product managers and executives must study in order to make the most appropriate decision.

 

“Build, buy, partner” is a strategic decision

For many vendors, IoT means adding a technology layer to products that never had any before. Even for tech savvy vendors, IoT presents a whole new set of technologies that they are less familiar with. Equally important, IoT is not just technology, but includes data, security, user experience, and business/business model elements. Figure One shows an IoT product management framework developed by Daniel Elizalde of TechProductManagement. A company going “smart” has a lot of decisions to make, of which technology is just one component.

Figure One. IoT Product Management Stack.

The framework shows that the “build, buy, partner” decision is multi-dimensional. There are six decision areas, spread across components from the edge to the user applications. Each represents a different “build, buy, partner” decision point, and each takes the company down a different path. In today’s fragmented and dynamic IoT ecosystem, many companies will need to “build, buy, partner” simultaneously. For example, cybersecurity is a specialized field that many vendors cannot address on their own, and must buy or license for their solution. The actual proportion of “build, buy, partner” each vendor does varies based on their specific situations.

Build

The company creates the solution themselves with the resources they own, control or contract to. Companies who choose this option, but have limited internal expertise may contract with Original Design Manufacturers (ODM). These ODMs provide a portfolio of services, from design, prototyping, test, certification, to manufacturing.

The “Build” option enables full management oversight of the development process, the solution functionality and the intellectual property. Conversely, this option may result in a longer time to market, and require additional capital and resources beyond what is scoped.

Companies consider this approach when:

  • They have the requisite skill sets and resources to do it
  • They can do it faster, cheaper and at lower risk
  • This is a strategic competence they own or want to own
  • There is strategic knowledge or critical intellectual property to protect
  • They are fully committed throughout the company

Buy

The company procures all or part of the solution components from a 3rd party. This includes licensing technology and services. Companies may also acquire technology through mergers and acquisitions, as well as buying the rights to technology from companies willing to part with it. This option eliminates “reinventing the wheel”, enables faster time to market, maximizes resource efficiency with limited execution risk. One common variant of this approach is to buy technology platform from a vendor, and then build their specific solution components on top of that. 

The downsides of the “Buy” option include a loss of control in the development process, and limited agility to respond in a timely manner to changes in the market and customer needs.

Companies consider this approach when:

  • They don’t have the skills or resources to build, maintain and support it
  • There is some or all of a solution in the marketplace and no need to “reinvent the wheel”
  • Someone can do it faster, better and cheaper than they can
  • They want to focus their limited resources in other areas that make more sense
  • Time is critical and they want to get to market faster
  • There is a solution in the market place that gives you mostly what you want.

Partner

The company allies itself with a complementary solution or service provider to integrate and offer a joint solution. This option enables both companies to enter a market neither can alone, access to specialized knowledge neither has, and a faster time to market. This option adds additional management and solution integration complexity. For some companies, reliance on partners for some aspects of the solution may be uncomfortable due to a limited loss of control.

Companies consider this approach when:

  • Neither party has the full offering to get to market on their own.
  • Each party brings specialized knowledge or capabilities, including technology, market access, and credibility.
  • It lowers the cost, time and risk to pursue new opportunities

 

Management considerations for “build, buy, partner”

Before the company chooses a path to go “smart”, executives and managers must base their decision along three “build, buy, partner” dimensions – execution, strategy, and transformation.

Execution

The first dimension focuses on the company’s ability to execute successfully. Managers must audit and assess their capabilities and resources to answer the following questions:

  • Do I have the necessary skills in-house to successfully develop, test, support and operate an IoT enabled “smart” solution and business (Figure One)?
  • Do I have the right human, capital, financial, and management resources to do this? Is this the best use of my resources relative to other initiatives and projects?
  • What am I willing to commit, sacrifice and re-prioritize to see this through? Am I willing to redeploy top management and company resources? How long am I willing to do this?
  • How much budget and resources am I willing to commit?
  • Is there anyone that can do it better than me? Does it make sense for me to do it? What am I willing to do and not do?
  • What infrastructure (processes, policies, systems) do I have, or need to build, maintain, support and operate these new solutions?

Strategy

The second dimension relates to the company’s current and future strategic needs. These are company specific as it relates to its current situation, its customer and channel, and its position within the industry. Key considerations to be addressed include:

  • How does going “smart” align with the company’s vision and strategy? Which parts align and which doesn’t? Does the vision and strategy need to be updated to reflect the realities of going “smart”?
  • How important is time to market? Do I need or want to be a first mover? How long will it take to execute with the resources that I have?
  • Am I trying to reach existing or new markets with IoT? Do I understand their needs well enough that I can execute on meeting it?
  • Do I have any critical proprietary technology, processes, and other intellectual property that I need to protect?
  • What are the risks? How much risk am I willing to tolerate? What are the costs of those risks? How much risk can I mitigate with my current capabilities?
  • How much control do I want or need to go “smart”? What areas do I want to control myself and how? Can I afford to control those areas?
  • What is your real value to customers and your channel? Why do they buy from you, and why do they come back? What do you do well?

Transformation

The third dimension is the company’s ability to manage transformation. Going “smart” doesn’t stop with the IoT technology. The entire organization, its operations, policies, systems and business models must transform to support and operate the “smart” business. Furthermore, resellers and service channels, and suppliers and partners, are also impacted.

  • What is your corporate culture and how well does it support change? Do you have the right people to manage and sustain this change? Are you nimble and agile?
  • What degree of disruption will there be to internal processes, channels, organization readiness, and business models? How agile are your current capabilities?
  • How prepared are you to operate a “smart” business? Do you have the skills and infrastructure required? Can you support a recurring revenue business model? How willing are you to invest in order to develop and sustain these capabilities?

 

What should you do next?

Each company is unique, and its situation will dictate its response to these dimensions. There is no one “right” universal answer to the “build, buy, partner” decision. Equally important, what’s right today, may not be right tomorrow. Companies that want to go “smart” start by looking inward first and doing the following:

  • Establish a current baseline. Audit and catalog current and planned offerings, strategy, human resources and skill sets, channel and suppliers, internal operations and policies, and culture.
  • Evaluate the IoT product management stack (Figure One) against your baseline using the three “smart” dimensions. The list of questions listed are starter questions, but answering those will lead to more questions to be addressed.
  • Evaluate and assess your company’s future state capabilities against the baseline using the three “smart” dimensions. Understand where the gaps are, and the extent of those gaps.
  • Identify your risk tolerance level. Going “smart” is not without risk, especially if you have never done it before. The key is to identify what and how much risk you are willing to take. Once you do so, you can develop a risk management plan and incorporate the appropriate tactics to manage it.
  • Update your business vision and strategy as applicable.
  • Develop your “build, buy, partner” decision and strategy. This strategy must align to the broader business vision and strategy.

 

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

Read more…

IoT Cyber-Security Puzzle

Image courtesy: Pixabay

I recently attended one of a significant [email protected] Internet of Things event which featured keynotes, speeches and presentations from CTOs/SVPs-Tech/VPs of major IT firms. Attending these presentations sometimes give you a feeling of being in literature or a rhetoric club where instead of hearing context oriented speeches you get to listen to a bunch of fairy tales with almost every sentence including overused adjectives like “trust”, “motivation”, “responsibility” and so on.  An SVP of a major IT player was asked about the measure (technical) her company takes to ensure data integrity and prevent cyber-attacks. Interestingly, her answer to this was the statement that “they maintain a culture of trust in and around the company”. To me, it is like standing in front of a hungry lion and telling him that you believe in non-violence. Today in the age of internet and IoT, we have to deal with thousands of cyber criminals (hungry lions) who are waiting to penetrate the system and make most out of it. To keep them out you need a lot more than just “trust”.  

On the same event, I had an opportunity to talk to many cybersecurity experts and companies, and I confronted them with a question of mentioning at least one relevant cybersecurity norm/standard/certificate pertinent for each major component in an IoT stack. Unfortunately, most of these discussions turned into some sales pitch. The question one can raise at this point is that is it so challenging to mention at least one “state of the art” cybersecurity measure for every IoT component? Or just that the topic is underestimated? 

This blog is just an attempt to name a relevant security standard/certificate or measure for every major element in IoT stack (see below) without going deep into the details of each and very standard/norm or certification. 

For this sake, we will assume a simple IoT stack as illustrated below :

 

Fig.1: IoT stack of a simple use case

In this use case, an industry sensor collects the physical parameters (temperature, pressure, humidity etc.) and transmit the values via Bluetooth/Wifi/wired connection to the gateway or edge device. The gateway device, depending on the type (simple or edge) perform a certain minimal calculation on the received data and push it into the cloud via a Wifi/4G connection. The cloud collects the data and uses this data to feed desired micro-services like analytics, anomaly detection etc. Cloud also offers an interface to the existing enterprise and resource planning (ERP) system to synchronize the running process with the current one as well to provide product /service related information over the IoT platform to the end user. What the user sees on his screen is then the dashboard of IoT use case which is a graphical representation of the micro-services running in the background. 

As we can see, there are four to five main stages and at least three interfaces (sensor-gateway, gateway-cloud, cloud-user) in a typical IoT use case. These stages and interfaces are on the target of cybercriminals who try to hack into the system with the intention of either manipulating or hi-jacking the system. Safeguarding just the components is not adequate. The underlying IoT communication layer (Bluetooth/Wifi/4G etc.) need to be secured as well.  Also, organisations running or involved in such IoT use cases must ensure safety and integrity of the process, technical as well as user data through a certain information security management system (ISMS) in place. 

To sum up, we need security measures at a component, communication-interface and organisational levels. Now if I have to write state of the art or “best in class” security measure (excluding cryptography) next to each stage, communication type and interfaces in the diagram above, then the resulting picture might look like the one below. 

 

Fig.2: IoT stack with relevant cyber-security measure

 

What, in your opinion, could be included/excluded or replaced in this diagram? Feel free to share your opinion.

 

Read more…
RSS
Email me when there are new items in this category –