The hopeless search for yourself 2.0 IoT and self-measuring

IoT and self-measuring

The hopeless search for yourself 2.0

Measuring yourself is definitely in fashion - but not everything you want to measure, can be measured; and not everything that can be measured, should be. A glance at the construction site called quantified self.
Still 2,000 steps to go, but already 400 kilocalories beyond the daily target; maybe head for the bike today instead of the TV? That would also benefit the energy consumption statistics, which was definitely lower last week, anyway.

Sorting yourself out

Apart from the self-filling refrigerator, self-tracking might be one of the core examples for push of the internet of things into our daily routines. The term "quantified self" was used for a website in 2007 by two US-american journalists of the magazine "Wired" and was applied to the tracking of passionate groups' individual dietary habits.

The recorded data provides subjective added value for the user, who oftentimes is willing to provide their data to industrial processing, probably without even recognizing it..

By now, athletes and health-conscious people are part of the quantified self-movement as well as entrepreneurs, the critically self-reflecting and the chronically ill - we measure, what we can measure. And the more everyday devicecs communicate with each other, the deeper the analysis.

In doing so, tracking tries to find its balance between steady self-optimization with questionable options of a target definition and the industrial usage due to the generation of added value from the willingness of people to reveal their data.

The reward is the journey

The curiosity to measure, analyze and evaluate yourself is all too reasonable. People want to know who and what they are, they want to improve, reach their goals and define new ones; a process, that can be motivating, but hardly satisfying. As soon as we have reached a defined goal, we either want to a) stick to it or b) define a new one. Both options lead to ongoing self-tracking. If you have reached your goal (e.g. reducing weight), you are in an intermediate state - in order to keep the weight down, you need to constantly observe, act and react. A final state is hard to be obtained here.

The science of numbers

Even if you are your own statistics, you can still be statistically abnormal.

Analyzing yourself due to quantifiable numbers is often seen as the basic motivation of the "quantified self" movement. Human assessments and decisions are oftentimes made by gut feeling, but having them substantiated with numbers can give a much more secure feeling. This is valid for your own body as well as your home or your office. The more individual the data, the more precise the tracking analysis. Right?

Overall, scientific and medical studies are based on a big number of study participants. The individual's results can lie within the norm but can also be exceptional. There's hardly a more precise result than when the basic quantity is n=1. Too bad that the data that is used to draw conclusions in order to class the significance of n=1 still comes from n=x. My blood pressure might not show the optimal value for my age, weight and activity range - this does not necessarily mean, though, that the value is definitely bad for me.

Let's get to self improvement

It almost seems mundane, how the established fitness tracking gadgets combine height and weight of the athlete with the frequency and duration of their workout, blood pressure and heart rate to provide a smorgasbord of data, statistics and charts. A lot of vendors offer similar features in their products - differing from each other in design only and, thus, oftentimes in pricing, too.

Fitbit, for example, is offering eight different, portable tracking gadgets by now, that serve clients of all sorts, from the occasional promenader to the marathon recidivist. Starting with a pedometer and sleep tracking, all the way through to continuous heart rate measurings, text notifications and audio controls, no desire remains unfulfilled.

Knowing your own desires, by the way, is not even necessary anymore due to the abundance of products and services. Who would have known that - after weight, user recognition, percentage of fat and heart rate - the next logical function of a weighing scale would be air quality? This is why the company Withings has integrated a carbon dioxide sensor into their smart body analyzer (which is only available on Amazon by now). All right. Right?

Nonetheless unconventionally, the HAPIfork is devoted to a healthy lifestyle; the smart fork's inventors take a closer look at the speed of eating and expect that to lead to an improvement of your individual wellbeing and health. Therefore, the fork tracks the speed, duration and frequency of eating during a person's meals and sends an alarm if they eat too fast, too often or too much. Despite the slogan "Eat slowly. Lose weight. Feel great!" it seems like the inventors do not care about one minor information: the food that is being eaten. It doesn't matter if it is salad, chocolate cake or steak - as long as you're eating it slowly.

Measuring for the sake of measuring

The complex area of the "internet of things" shows a lot of potential that, nevertheless, seems to lead to mostly similar areas of application, usage and technologies. On the one hand, this is perfectly understandable, since some products have been proved and established and niche products contain a lot of risks; on the other hand it's a pity, since useful, well thought out usecases are not brought into being.

Without appropriate logic and connections, the quantity of factor A oftentimes just remains to be the quantity of factor A.

One other fact reduces this monotony to absurdity all the more: not everything that people want to measure can be divided into quantifiable values that easily. Physical features (heart rate, blood pressure, body temperature, sweat production etc.) or objectively measurable factors (outdoor temperature, water level, amount of calories or minerals etc.) have a meaning that can be connected to their individual characteristics. But, in order to measure abstract terms, it's not enough to combine various allegedly meaningful aspects; someone who writes a lot of emails is not necessarily productive; someone who sleeps a lot is not necessarily relaxed; and someone who has a lot of friends on Facebook is not necessarily an extroverted, outgoing person.

The point where self-measuring does indeed benefit someone is in cases where the acquired data can help the vendor to customize his offer for the individual or verify statements that affect pricing or services. The huge subject matter of data protection shall not be treated here, though. It might be sufficient to say that insurance companies can, by now, motivate their clients to live a healthy lifestyle and get cheaper rates in return. The potential consequences of reducing the workout intensity or gaining weight after a few months or years are a whole other topic.

What remains is the question of combining possibilities and logic. We can measure a lot of things, but we still want to know more; not everything should be measured, though, and transformed into a digital brand mark; and not everything suddenly gets useful just because it is technologically combined.