The value lies in the data

Text written by Jan Nyrén, Product Manager IoT technologies, at IAR Systems

A question that often comes up when people from the embedded industry are talking about the new connected world is: "what’s the big deal with IoT and why all the fuss?"

Well, it depends on how you decide to look at it, either with a conventional M2M view or with an IoT view. In the embedded industry, many are saying "We have had solutions with remote connectivity deployed to achieve productivity gains, reduce costs and increase safety and security for years. OK, we will see billions of new devices, but what is the fuss about, really?"

From one angle there is not that much of a difference compared to today; we will use the same technologies, a sensor, an actuator and a wired/wireless connection together with a microcontroller will still be the building blocks of the devices in an IoT solution, so nothing new there. (This view is what I call the “conventional” M2M view.)

From another angle, the IoT has the potential to become a revolution with the same impact as the internet once had, with the power to transform our everyday life as well as how we do business. Potentially, it can drive growth globally for a number of years ahead. It all boils down to how we can leverage on the generated data and use it in a smart way. With data, I mean not just the data produced by the sensors in future IoT solutions but also data generated elsewhere, for instance in social media.

The conventional Machine-2-Machine

In the conventional M2M paradigm, devices sense the physical surroundings and communicate with other devices that are part of the same application or with a central server. All applications are managed as silos, meaning that there is no direct way to share the generated data directly to the internet or with other parties. Many of these applications use proprietary methods for communicating, managing the devices and for storing the data.

The Internet of Things

In the IoT view, the information generated will be connected and accessible by the broader internet. The vision is to enable things and real world objects to connect, communicate, and interact with one another in the same way as humans do via the web today.

Once the data is on the internet it can be aggregated with information from other sources such as GPS data, road databases and weather data, as well as for example data personal data extracted from social media. From there it can be shared with other stake holders, who are in need for specific data for their specific application.

An illustrative example

In the book “From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence”, Jan Holler et al, discusses how the new way of looking at IoT will unleash the potential. An illustrative example shows two different approaches towards a solution to the same problem, namely individual stress monitoring. Studies have shown that close to 50% of the health risks of the enterprise workforce are stress related. Measuring of stress can be done using sensors. Two common stress measurements are based on heart rate and galvanic skin response. There are products on the market today in the form of bracelets that can do such measurements and even add information about the person’s movement from an integrated motion sensor.

In the conventional, silo-M2M world, the solution would be based on getting sensor input from the bracelet and sending the data to a central server for analysis. Although the central server can do a lot with the information, it does not have sufficient data to answer the question about what actually was causing the stress.

In an IoT world on the other hand, more data would be available that would provide deeper and much richer information of the person’s contextual situation. Information that could be useful and potentially mined in addition to the direct information from a bracelet is

  • weather and environment such as level of light, temperature, level of pollution, etc.
  • home environment such as temperature or noise level.
  • work environment such as work hours, level of noise, number of unanswered emails, etc.
  • commuting experience.
  • leisure activities.
  • specific happenings in the society.

The more data that is available, the more can be analyzed and correlated in order to find patterns and dependencies.

Challenges

What is obvious is that the technology used may be the same in the M2M and the IoT (at least on the device-side of the solution), but the manner in which data is managed will be different. Not just technically but also on a business level. What is required is therefore also the advent of new business models with regards to the data. In M2M, the data is used only by the producer of it. In the IoT world, data can be shared, used and reused for many different purposes. This is where the benefits, but also the challenges lie - for instance:

  • How can data be shared in a safe way and handled with integrity? It is obvious that sensitive information such as for example patient data must be handled with greatest care and there must be mechanisms to ensure that this type of data never can be compromised throughout its lifetime. Nor that the integrity of the person owning this data is compromised.
  • How can data sharing be incentivized? This will probably require data platforms to emerge where companies and end users can trade in data in a simple way.
  • How can the massive amount of data be processed in an intelligent way? There will be a previously unseen amount of data generated and the challenge is to acquire, validate, store, process and analyze it in an efficient and intelligent way.

All of the challenges mentioned above are being addressed as we speak. Below is a list of initiatives where focus and effort is being spent throughout the industry at the moment.

  • Big Data initiatives as well as data analytics. This is a topic that has been hot for several years, and all the big database vendors and social media companies are competing for the most efficient storing and analyzing of data.
  • Information Driven Global Value Chain (I-GVC). The definition of a value chain where the commodity is information, not oil or gold as one may be used to, is currently being mapped out. This will likely take time to settle, but it is critical in order to stimulate and incentivize the production of relevant data.
  • Data security and integrity of data throughout its lifetime. Security is one of the hottest topics in IoT. The way to handle data securely in an I-GVC still needs to be ironed out.

To me it is obvious in what direction the industry is going; the IoT direction. The road there may be long and not always straight but with all the possibilities that we see, I am convinced that there is enough collected enthusiasm and force in the industry to make it happen.