Using Radar to Read Body Language
Yet another method of surveillance:
Radar can detect you moving closer to a computer and entering its personal space. This might mean the computer can then choose to perform certain actions, like booting up the screen without requiring you to press a button. This kind of interaction already exists in current Google Nest smart displays, though instead of radar, Google employs ultrasonic sound waves to measure a person’s distance from the device. When a Nest Hub notices you’re moving closer, it highlights current reminders, calendar events, or other important notifications.
Proximity alone isn’t enough. What if you just ended up walking past the machine and looking in a different direction? To solve this, Soli can capture greater subtleties in movements and gestures, such as body orientation, the pathway you might be taking, and the direction your head is facing—aided by machine learning algorithms that further refine the data. All this rich radar information helps it better guess if you are indeed about to start an interaction with the device, and what the type of engagement might be.
The ATAP team chose to use radar because it’s one of the more privacy-friendly methods of gathering rich spatial data. (It also has really low latency, works in the dark, and external factors like sound or temperature don’t affect it.) Unlike a camera, radar doesn’t capture and store distinguishable images of your body, your face, or other means of identification. “It’s more like an advanced motion sensor,” Giusti says. Soli has a detectable range of around 9 feet—less than most cameras—but multiple gadgets in your home with the Soli sensor could effectively blanket your space and create an effective mesh network for tracking your whereabouts in a home.
“Privacy-friendly” is a relative term.
These technologies are coming. They’re going to be an essential part of the Internet of Things.
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