A (Simple or Not-so-simple) Introduction to the Internet of Things

Excel Chukwu

2022-08-05 (Updated: 2023-03-05)

This is a republishing of an article I wrote and puclished on my previous site.

Many articles have been written about the Internet of Things, and many of them are really good (see here). Articles and courses exist that will explain the intricacies of the internet of things, such as hardware, network protocols, energy considerations, etc. An example is this really detailed course from Stanford. The goal of this article is to explore IoT from a perspective which, while spoken of, is not emphasized a lot: data.

A little history

Before I dive into IoT from the perspective of data, a little history. The world up to now has gone through a number of industrial revolutions. The first industrial revolution introduced mechanization; the second that brought electrification; the third brought about a focus on energy, a rise in telecommunications and electronics, and biotechnology. We are currently undergoing the fourth industrial revolution, or Industrie 4.0, and with it has come the ubiquity of technology and automation. Perhaps most importantly, it has brought with it the proliferation of data and information. As such, it is referred to the the information age. The proliferation of technology has led to a massive reduction in the cost of technologies that have now made IoT possible, not to mention the reduction in the barrier of entry for people looking to get started in these new areas.. For a more detailed history of IoT and the technologies that have made it possible, see this article and this article.

A formal definition

The internet of things is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided unique identifies (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction¹. That’s a mouthful…and not-so-simple (see what I did there?)

A simpler definition

A simpler definition of the internet of things could be that it is just a connection of billions of devices (that can be anything), which are able to communicate with each other and with the Internet. These devices (things) are embedded with sensors or actuators that help them read data from their environment, communicate what they read, and act based on these readings.

IoT and Data

Now, back to IoT and data. When you hear IoT, think data. This might come across as a bold statement or an oversimplification of the technologies like sensors and cloud computing that make IoT possible. My aim is not to minimize the great strides that have been made in these areas. However, thinking of it from the end-point looking back, it…just makes sense. What is the goal of making these things ‘intelligent’ and able to communicate? That is meant to be a rhetorical question, but I’ll answer it. At the risk of stating the obvious, the end-goal is data (and making sense of it of course).

Our modern world is data-driven, and as the world becomes more interconnected and data more disjoint, what will help us make sense of the chaos is analyzing data and making decisions off it. But we cannot analyze data without collecting it. Without highlighting the ethics of how the data is collected, we know that it is companies that are able to collect the most data and make the most sense of it that are most valuable.
This is the premise of companies like Palantir, which builds its products on the premise that the world will become more ‘unhinged’ and disjoint (watch CEO Alex Karp talk about it). Managing and making sense of complex data is one of the keys to maintaining structure and retaining a competitive edge in whatever industry a company plays in.

With the outset of these huge amounts of data, there are a number of considerations that are paramount for IoT:

We need tools to help us store the massive amounts of data in a secure way. Examples of such a tools are Amazon Redshift, Google BigQuery and Microsoft Azure.
We need tools to help manage and analyze large-scale data to help organizations unlock insights into their industries or customers. The data warehousing tools above also provide analysis, but additional tools for data analytics include Apache Hadoop, Kafka, etc.
Common communication protocol: different media pose different challenges when it comes to networking, and as everything becomes interconnected, there needs to be a commonly understood protocol for communication among these devices. Obviously, one might say, we have the Internet, HTTPS, TCP/IP, etc. That is true, but different devices will have different implementations that can pose challenges to how the known protocols are used. In addition, the additional constraints we have on these unconventional devices increase our considerations for how known protocols are implemented on IoT devices. This is the reason for the need for a unified communication protocol. Such a protocol might still be afar off, though. There is a host of network protocols that have made it easier to connect these devices to larger Internet, they work just fine.
Security and Privacy: security is perhaps the biggest concern in the adoption of IoT, despite its ability to yield increased ROI in a company as outlined by this Siemens Advanta paper, or to improve the lives of consumers. Questions such as, “How secure is the data” and “Who owns the data”, are valid concerns because like every technological trend or buzz word, it is easy to adopt or build IoT solutions without thought for security and privacy. As solutions, manufacturing principles such as privacy by design can increase the security of IoT devices, as can securing network communication using innovations like blockchain.

Conclusion

I have tried explained the internet of things with a focus on data in a simple way. I outlined a bit of the history of ‘industry’, and explained why the overarching goal of IoT is data. I also listed some considerations for IoT that can aid its adoption. It is often the case with modern technology that massive adoption is pushed before considering the wider implications.

“It is important for software engineers to think of the wider implications of their work.” - Ian Sommerville

Likewise, with the increasing amounts of data and the adoption of internet of things, we must stop to consider these wider implications and consider how we might mitigate compromises of data before they occur.

*The purpose of these technical blogs is to explore topics I am interested in, explain them the way I understand, and share my knowledge with others

If any errata are spotted in this blog, please contact me through my site and I will update them.

Additional Readings

Written with StackEdit.