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Wearable sensor tracks user’s carbon footprint

Wearable sensor tracks user’s carbon footprint

By eeNews Europe



Dubbed "MagnifiSense," the technology is designed to enable a user to track their individual "carbon footprint" throughout a day as they interact with various devices and machines. According to the researchers, a calibrated prototype system was able to correctly classify 94% of users’ interactions with a dozen common devices including microwaves, blenders, remote controls, electric toothbrushes, laptops, and light dimmers, as well as vehicles like cars and buses.

Designed to be worn on a user’s wrist, MagnifiSense uses the unique electromagnetic radiation signatures generated by electrical components or motors to identify when its wearer turns on a device or appliance, or even uses or boards a motor vehicle. Even without calibration, the system was said to be able to accurately classify an interaction about 83% of the time.

"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," says Shwetak Patel, Washington Research Foundation Endowed Professor of Computer Science & Engineering and Electrical Engineering, and director of the UW Ubicomp (ubiquitous computing) Lab. "Right now, we can know that lights are 20% of your energy use. With this, we divvy it up and say who consumed that energy."

The prototype wearable system comprises three off-the-shelf passive magneto-inductive sensors and an analog-to-digital (ADC) circuit. Its frequency range and algorithm enable it to differentiate between electromagnetic radiation emanating from the unique combinations of electronic components – such as motors, rectifiers, and modulators – embedded in everyday devices.

"When a blender turns on, for instance, modulators change the current profile of the device and create something similar to a vocal cord pattern," says Edward Wang, a UW electrical engineering doctoral student and a lead author of the study. "A blender ‘sings’ quite differently than a hair dryer even though to our ears they sound similar."

The researchers plan to test MagnifSense on a wider range of devices and to further improve its ability to distinguish among devices operating in close proximity, as well as find ways to shrink it down in size to that of a watch or wrist band. For more, see the paper describing the study: MagnifiSense: Inferring Device Interaction using Wrist-Worn Passive Magneto-Inductive Sensors (PDF).

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