Tell me more Internet of Things — Part 1 —  IoT platform cost and value comparison

The full article was originally published by Jan Bertrand on Medium. Read the full article here.

Tell me more Internet of Things — Part 1 — IoT platform cost and value comparisonComparison of selected IoT (Internet of Things) AEP (Application Enablement Platform) by implementing step by step a specific use-case and adding a possible DLT (Distributed Ledger Technology) implementation to that comparison.

This article (Part 1) explains the project goals. I am introducing the use/business case and how I intend to compare the cloud implementations. At the end we will set up the hardware of the use-case and deploy a simple program which prints the sensors data to the command line.

This is my personal project (multiple parts) which could stretch along month.

Motivation and targets

According to Gartner Hype Cycle the Term IoT Platform is just about on its decline from its hypest and highest rise.

Adapted Gartner Hype cycle with IoT Platform and Blockchain as of July 2018. Yin Yang symbol (describes how seemingly opposite or contrary forces may actually be complementary)

Even though Gartner is not necessarily right about every detail in technology it is certainly true that there is loads of positive business outlook from the very same research team states several trillion industry in just a few years (yes trillion 1,000,000,000,000 ?)

True is as well that many companies have already opened their devices/businesses to the internet. And some made the collected data analyzation and data visualization centrally to their value proposition.

Whereas companies like Siemens focus in some parts more on the industrial business with their own platform MindSphere, which states to be the Operating System (OS) for the Industrial Internet of Things (IIoT). Others like Google (Google Cloud) or Amazon (AWS) added specially IoT to their vast cloud functionalities in order to advertise this market better.

All of these platforms have in common that they are offered as services. Whereas Siemens MindSphere is a Platform as a Service (PaaS) — Google and Amazon bring the Infrastructure as a Service (IaaS) included in their offerings. Meaning Siemens won’t have their own Servers (Data Centers ~ Clouds) but need to partner up with Microsoft, Amazon or Google.

The maverick approach for IoT combines two of the most hyped topics — IoT and Blockchain (better DLT Distributed Ledger Technology) and with that it would be on the highest hype on that very same curve. IOTA stands for (“A permissionless distributed ledger for a new economy”) — it’s not really the abbreviation I was expecting but it makes sense ?. We have to be fair here, IOTA is not a platform but rather a protocol.

So adding IOTAs distributed and decentralized approach to the comparison is risky but I think worth it and opens up to a lot of questions and discussion while comparing to centrally managed platforms.

Currently IOTA transactions (messages) are secured by distributed Node software running on personal servers or cloud instances (VPS). So it is neither a IaaS nor a PaaS — it enables with providing node software, the protocol as well as a wide community to promote their vision of IoT.

All IoT solutions have in common beside other things like security, data handling and automation to solve scaling.

But why do we need all that scaling?

The control theory and system identification Professor emphasized us to always apply the most simple and easiest approach before going nuts (meaning just try linearly identify a system before training nonlinear neural networks). Translated to our use-case here that would be starting not necessarily with the BigData approach ?. The use case (product) we will develop is at the time of writing just one device and we could implement it very easy non scale-able way. Knowing that without the other ~9.999 devices we won’t have any way of doing big data diagnostics which is the real value contribution for the business case.

In order to understand the IoT platforms benefits but as well its drawbacks we define a business case for our product (use-case) to understand how the value proposition develops with those increased functionalities.

  • Use-case: The product we connect to the IoT “platform”.
  • Business case: How to make money with this product/service connected to the cloud?
  • Value proposition: What is in for the customer?

The reference architecture

To structure our approaches and use the same wording we follow the reference architecture for IoT systems introduced by the Institute of Architecture of Application Systems.

Read the full Article

The full article was originally published by Jan Bertrand on Medium, where people are continuing the conversation by highlighting and responding to this story.

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