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The sensor board can be plugged in to a wall outlet, eliminating the need for batteries.

Researchers have developed a sensor package that monitors multiple phenomena in a room using machine-learning techniques. The prototype contained 19 different sensor channels, including sensors that indirectly detect sound, vibration, motion, color, light intensity, speed, and direction. The sensor board is plugged in to a wall outlet, eliminating the need for batteries.

After developing the prototype, the team gave the sensor “training” data by providing it with hundreds of real-world examples of what 38 different devices and appliances sound like when in use. Once the sensor “learns” this data, it can then be presented with a new object where it can pick out what it is, based upon the 38 patterns it’s already recognized.

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