The Internet of Things (IoT) is heralded as the fourth industrial internet, and participate in machine-to-machine and machine-to-person use cases on a massive scale. The common trait of all these IoT use cases is to efficiently handle the following essential jobs: connecting and managing billions of devices, transferring data over the network, storing data, and processing data. Apparently, data has a central place, so we may freely announce that IoT is data-driven. Computing associated with data is there to squeeze out knowledge, and provide the ability to automate many aspects of our environment. The objective is to deliver new value-added business services that were not possible before.

Any cutting-edge technology/paradigm, like IoT, is surrounded by a vivid, dynamic, and growing community. The participants seek to gain knowledge and experience in the novel domain. The interrelated environment is permeated with various overlapping technological alternatives that are frequently accompanied by hype. It isn’t surprising then to encounter terms like Massive IoT, Industrial IoT, Critical IoT, Web of Things (WoT), and Internet of Everything (IoE). Furthermore, we encounter stuff like digitization on one hand, and Invisible Computing, Transparent Computing, Edge Computing, and Fog Computing on the other (these are some of the most popular phrases). Our aim is to find a common denominator among these elements, rather than delve into a convoluted elaboration of how to properly classify them.

For example, in terms of device connectivity we may classify low-power network technologies into the following broad categories: unlicensed spectrum for short-range and mixed-performance communication (WiFi, Bluetooth, Zigbee, etc.), unlicensed spectrum for mixed-range and low-performance communication (SIGFOX, LoRa, etc.), and cellular for mixed-range and mixed-performance communication (EC-GSM, LTE-M, NB-IoT, etc.). Regardless of which category they belong to, all of these technologies seek to balance dependability, performance (throughput and latency), and cost/complexity. If you want to learn more about how cellular networks are adapted to the needs of IoT, read the Ericsson whitepaper Cellular Networks for Massive IoT.

A principal enabler of massive adoption of IoT use cases is the existence of an efficient IoT platform. It combines device connection/management and service enablement functions. It may be treated as a key building block in IoT solutions. Custom applications are crafted on top of an IoT platform that handles all the mundane work regarding devices as well as data analytic capabilities. An IoT platform is like middleware for distributed applications. IoT platforms are the topic of this report, and are superb examples of scalable architectures for IoT. For a good commentary about the importance of IoT platforms and data management in IoT, refer to The Platform Transformation—How IoT Will Change IT, and When by Matthew J. Perry (O’Reilly).

It is impossible to provide exhaustive coverage of IoT platforms in this short report. Instead, we have chosen to focus on the following goals:

  • Teach you how to become proficient with some concrete IoT platforms.

  • Help you sharpen your knowledge by suggesting many references for further study.

  • Offer different perspectives on IoT topics.

  • Provide some comparative analysis between various industrial IoT platforms.


This work is structured as a report rather than a full-blown book. Consequently, its content is presented in a condensed form with many references for further reading. We have tried to provide enough content for you to understand the material even without consulting outside resources. Nonetheless, to gain deeper knowledge you will need to review the various books, webinars, and blogs we highlight throughout this report.

Contents of This Book

This report is comprised of five chapters:

Chapters Chapter 2 through Chapter 5 follow a similar outline, and a table is provided at the end of each of those chapters to summarize the IoT platform discussed therein (using the set of evaluation criteria set forth in Chapter 1). There is also a Conclusion that wraps up this report.

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