THREE ISSUES FACING THE INTERNET OF THINGS

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The potential of the internet of things is enormous. While we might still be some years away from the technology reaching its zenith, the effect it is already having on our everyday lives is huge; from assisting the disabled to monitoring our health, the internet of things is slowly starting to deliver on its promises as a life-changing development. 

Despite that, there are issues. The sooner the internet of things can negotiate and solve these issues, the sooner it can develop in a smooth and efficient manner… 

1) How many devices can one person wear? 

Is it realistic to expect one person to wear ten different devices? Twenty? Fifty? The current trend in technology products is for new launches to be both simple and ready-to-use – the result is that most devices are designed to do one thing really well, and not much else. The knock on effect is that there is an over-specialisation occurring, for example, a wearable that only monitors your sleep, or only monitors how fast you eat, or only monitors a certain aspect of your health. 

While blogger Harrison Weber managed to try on 56 different gadgets at CES 2015, you could never charge, manage and wear them all at once. 

The problem is linked to that which Samsung’s chief executive BK Yoon recently touched on – there has to be more standardisation, more cross-competitor collaboration, and more user-friendly product development. Without it, the industry will crash. 

2) Sensing or inferring? 

Linked to the previous problem, there is an increasing trend towards making devices seemingly for the sake of it. While CES might be swimming with smart yoga mats, clever skis, and intelligent light sensors – are they really necessary. 

A perfect example is that of the light sensor. For example – is a wristband which tells you how much UV exposure you’re getting deserving of being a standalone gadget? Could a smartphone not measure light levels, decide whether you’re outside, and check the UV index? The wristband is sensing, the smartphone is inferring. 

An example of a company which has adapted is Jawbone. Early versions asked wearers to log their activity manually, but newer models notice a period of activity, guess at what that activity was by comparing it to known patterns, and confirm it by asking the user. Your response will either reinforce or update its models of what particular activities look like. 

3) Linking data to actions 

As we discussed recently, an endless stream of raw data is not useful nor appealing to consumers. The consumer-side future of wearables is not about the data itself, but instead about using that data to create intelligent, useful, and actionable feedback; ultimately, if data doesn’t change your behaviour, then why bother collecting it? 

Consider stress monitoring apps, while the principle of seeing how stressed you were at a certain point in the day is a nice idea, unless you can see the person to whom you were talking, or revisit the situation you were in, it’s hard to do anything about it. The solution in this regard could be an amalgamation of life-logging apps with stress monitoring wearables – and solutions such as these would also address some of the issues noted in the aforementioned first point.