Cornell CIS

'VibroSense' Tracks House Appliances Through Vibration, AI

To boost efficiency in typical households – where people forget to take wet clothes out of washing machines, retrieve hot food from microwaves and turn off dripping faucets – Cornell researchers have developed a single device that can track 17 types of appliances using vibrations.

The device, called VibroSense, uses lasers to capture subtle vibrations in walls, ceilings and floors, as well as a deep learning network that models the vibrometer’s data to create different signatures for each appliance – bringing researchers closer to a more efficient and integrated smart home.

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