Wrist sensor tracks appliance use, monitors carbon footprint
A sensor worn on the wrist can sense what devices and vehicles the user interacts with throughout the day, which can help track that individual's carbon footprint and enable smart home applications, say scientists, including those of Indian-origin.
Washington: A sensor worn on the wrist can sense what devices and vehicles the user interacts with throughout the day, which can help track that individual's carbon footprint and enable smart home applications, say scientists, including those of Indian-origin.
The technology developed at the University of Washington, called MagnifiSense, in a study correctly classified 94 per cent of users' interactions with 12 common devices after a quick one-time calibration, including microwaves, blenders, remote controls, electric toothbrushes, laptops, light dimmers, and even cars and buses.
Even without the calibration, MagnifiSense was still correct 83 per cent of the time, researchers said.
The sensor worn on the wrist uses unique electromagnetic radiation signatures generated by electrical components or motors in those devices to pinpoint when its wearer flicks a light switch, turns on a stove or even boards a train.
"It's another way to log what you're interacting with so at the end of the day or month you can see how much energy you used," said Shwetak Patel, Washington Research Foundation Endowed Professor of Computer Science & Engineering and Electrical Engineering, who directs the UW Ubicomp Lab.
"Right now, we can know that lights are 20 per cent of your energy use. With this, we divvy it up and say who consumed that energy," said Patel.
In a 24-hour test in which a single user did everything from reading on a laptop to cooking dinner and taking a bus ride, the system correctly identified 25 out of 29 interactions with various devices and vehicles.
MagnifiSense also has potential for other smart home applications, such as recognising a user's preference for interacting with an appliance or device.
By sensing whether an adult or child is turning on a television or tablet, for instance, a system could automatically display their favorite programmes or tailor the device with appropriate selections.
In assisted living settings or nursing homes, the wearable sensor could help keep track of how efficiently elderly people are going about everyday tasks such as cooking or grooming.
It could also detect when a stove has been left on for a long period of time and help alert someone to that danger.
The team combined three simple, off-the-shelf sensors that use inductors, or coils of wire wound around magnets. Those proved to be the most accurate without being so power-hungry that wearing them would be impractical.
The sensors also capture a broad frequency range that allows the system to differentiate between electromagnetic radiation emanating from the unique combinations of electronic components such as motors, rectifiers and modulators embedded in everyday devices.
Co-authors of the study include UW electrical engineering doctoral student Tien-Jui Lee, UW computer science and engineering doctoral students Alex Mariakakis and Mayank Goel, and Sidhant Gupta.