The Internet of Things (IoT) has been in the news over the last few days, because an estimated 100.000 internet connected devices were used to launch a malicious distributed denial of service (DDoS) attack, bringing down sites including Twitter, the Guardian, Netflix, Reddit, CNN and many others in Europe and the US. But should we consider the Internet of Things as a blessing or a curse? Can we harvest the benefits without having to put up with the drawbacks?
Let’s start at the beginning, in simple terms the Internet of Things is “a network of devices that contain embedded technology to communicate, sense, and interact with the internet and other devices.”
In other words, it is a way for everyday objects to talk to each other and to you. For example, your refrigerator might alert your smart phone when the milk has run out. The forecasted numbers of devices are staggering. Cisco, the largest networking provider in the world, estimates the number of connected devices to reach even 50 billion by 2020.
From a mind+machine perspective, this opens up a whole new world of promising use cases, with millions of new data sources, connected directly to where the data is being processed. Most of the data from these devices comes in the form of simple sensor readings, such as: locations, temperatures, speeds, vibrations, pressures…etc.
Increasingly this data is streamed, for example a machine sensors might send temperature or pressure readings every few milliseconds or cameras stream video feeds in real time. Streamed data adds a new aspect to data analytics, as it is simply impossible for humans to be involved in the actual digestion of the data since mind is simply too slow to get involved at the streaming level, full stop. However with the right machine, this will allow you to get the information and even insights much more immediately.
So what is the role of the mind in use cases involving streaming data? When the tools required for a use case grow more sophisticated, it also becomes more important to focus on the development and the governance of the use case, and the usage of any Level 3 insights generated. ‘Use case engineering’ might become a new function, with people working on useful Internet of Things opportunities, creating or fine-tuning prototypes that work and discarding the ones that don’t, and then building production versions that run semi-autonomously, supervised by humans that are assisted by machines.
Regardless of how the use cases are managed, it is clear that opportunities in this fields are plentiful and very interesting. However the Internet of Things is still in its infancy in general and before all the promises can be realized, a few fundamental issues need to be addressed.
For the sake of brevity, I will have to skip the issues of liabilities, accountabilities and audit trails, but if you are keen to learn more about the Yin or the Yang of the Internet of Things or how mind+machine can help you exploit its potential, why not take a look at my book, where I discuss these topics in more details.