How to convert IoT into knowledge
Meanwhile, everyone knows the Internet of Things (IoT). Gartner estimates that in 2020, 75 billion objects were interconnected, versus 27 billion in 2019, or circa 5 devices per household. However, some of these connected objects are associated with human beings, such as smartphones, connected watches, GPS and trackers.
So far, the data collected by these devices haven’t really been exploited. Of course, the legitimate questions of privacy and security arise. But in fact, big data is what we are talking about here, rather than information. By 2023, however, it will be possible to digitally track more than 40% of the population, according to Gartner. That is no less than three billion people!
It should be possible to exploit all data. Of course, we immediately think of analyzing these data in order to determine purchasing behavior and to provide consumers with (more) targeted advertising. Some examples: the possibility of analyzing a person’s medical data within the framework of the treatment or prevention of a disease. In the professional world also, such IoT devices would allow to anticipate system failures, to proactively work on equipment maintenance, or to optimize the operation of a production line.
Consequently, the Internet of Behavior (IoB) aims to convert the data collected by all these devices in order to extract information and subsequently to deduce behaviors and decision trends. By ‘behavior’, we shouldn’t only understand the way an individual acts, whether in his private or professional life, but also how a machine or process works.
Besides, Gartner considers IoB as one of the ‘top strategic predictions for 2021 and beyond’ for IT directors in 2021. According to Gartner, by 2025, half the world’s population will be subject to an IoB commercial or government program.
Collect, process, analyze
Note that ideally, IoB should be part of an ecosystem of companies and not just involve only one organization. An example: an insurance company will be able to obtain data from a car manufacturer in order to ‘adjust’ the insurance contract to a specific driver. Likewise, it will be able to collect information from social networks, in particular to refine the profile of each policy holder. Indeed, the famous GAFA (Google, Apple, Facebook and Amazon) and other Internet giants (Amazon, Twitter, Alibaba and many more) are collecting lots of data about anyone of us. To put it shortly: the ‘big data’ is a reality.
Associated with automation, artificial intelligence, facial recognition and algorithm technologies, IoB is clearly opening up a new era, providing added value to the business.
IoB requires the implementation of appropriate infrastructure and tools. Although the cloud can appear as a solution to provide (temporary) additional processing capacity on demand, such a platform generates latency which is often incompatible with the needs of real-time processing. Moreover, IoB requires a certain computing power that is not always available in the cloud, especially in terms of data analytics, not to mention the number of users and devices involved.
In addition, an ‘edge’ type architecture should be promoted to allow data processing as close as possible to its source, i.e. most often, decentralized and mobile devices, which allows to reduce latency, to reduce the burden on the network and to limit the necessary resources at central level.
At the same time, it will be important to strengthen and secure the network, knowing that IoB (often) implies the processing of sensitive data.
Understanding the behaviors - of human beings and machines - by means of IoB clearly offers added value to the organization. Of course, the implementation of adapted tools and platforms is a crucial step for the success of such a project. But it is also important to surround yourself with the right skills, whether in terms of understanding the business or in terms of technical knowledge. Likewise, we can’t stress enough the importance of security and compliance, in particular compliance with GDPR (General Data Protection Regulation).
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