The Internet of Things (IoT) is a term spanning a variety of ‘smart’ applications. This ranges from things like smart fridges, to smart cities. This idea of ‘smart’ or IoT is the connectedness between everything and the internet.
It’s hard to grasp the amount of data one person creates each day and understanding where IoT fits into that. And with this new era of ‘smart’ everything, the realm of knowledge is pushed even farther away.
To understand just how much our smart technologies follow our everyday behaviours, let’s focus on only one person’s use of a smartwatch.
But first, what are the implications of a smartwatch? This wearable technology gained its popularity starting in 2012, giving users the ability to track their health and set fitness goals at the tap of their wrist. Since then, smartwatches have infiltrated all sorts of markets, from the ability to pay using the watch, take phone calls, or update a Facebook status.
The technology in our lives has become so interconnected, de-identifying our data, while achievable, on a grand scale, is seemingly complicated. Take the smartwatch, our unique footprints, recreated each day are logged and monitored through the small screen on our wrist. While the data created is anonymized to an extent, it’s not sufficient.
But why not? After all, technology has moved mountains in the last decade. To better understand this connectedness of our data, let’s follow one person’s day through the point of view of just their smartwatch.
Imagine Tom is a 30-year-old man in excellent health who, like the rest of us, follows a pretty general routine during his workweek. Outside of the many technologies that collect Tom’s data, what might just his smartwatch collect?
Let’s take a look.
Every morning, Tom’s smartwatch alerts him at 7:30 am to wake up and start his day. After a few days of logging Tom’s breathing patterns and heart rate, and monitoring his previous alarm settings, Tom’s smartwatch has learned the average time Tom should be awake and alerts Tom to set a 7:30 alarm each night before bed.
Before ever having to tell his watch which time he gets up in the morning, his watch already knows.
Similar to his smartwatches alarm system, this watch knows and labels the locations of 6 specific places that Tom spends most time in the week. Tom didn’t have to tell his watch where he was and why; based on the hours of the day Tom spends at this location, with his sleeping patterns and other movements, his watch already knows.
Not only are these places determined from his geographical location, but from the other information, his watch creates.
When Tom is at the gym, his sped-up heart rate and lost calories are logged. When Tom goes to his local grocery store or coffee shop, Tom uses his smartwatch to pay. At his workplace, Tom’s watch records the amount of time spent at the location and is able to determine the two main places Tom spends his time is between his home location and his work.
Based on a collection of spatial-temporal data, transactional data, health data and repeated behaviour, it is easy to create a very accurate picture of who Tom is.
Let’s keep in mind that this is all created without Tom having to explicitly tell his smartwatch where he is or what he is doing at each minute. Tom’s smartwatch operates on learned behaviours based on the unique pattern Tom creates each day.
This small peak into Tom’s life, according to his watch, isn’t even much of a “peak” at all. We could analyze the data retained by his smartwatch with each purchase, each movement of location or only by the data pertaining to his health.
This technology is seen in our cars, fridges, phones and TVs. Thus, understanding how just one device collects and understands so much about your person is critical to how we interact with these technologies. What’s essential to understand next is how this data is dealt with, protected and shared.
The more advanced our technology gets, the easier it is to connect a person based on the data the technology collects. It’s important more than ever to understand the impacts of our technology use, what of our data is being collected, and where it is going.
At CryptoNumerics we have been developing a solution that can de-identify this data without destroying its analytical value.
If your company has transactional and/or spatio-temporal data that needs to be privacy-protected, contact us to learn more about our solution.