Researchers at Carnegie Mellon University's (CMU) Human-Computer Interaction Institute have developed a plug-in sensor package that tracks multiple phenomena in a room, collecting insights via machine-learning methods.
"The idea is you can plug this in and immediately turn a room into a smart environment," says CMU's Gierad Laput.
He notes the raw feeds from the package's nine sensors can be integrated and read by machine-learning algorithms in ways that can perceive numerous phenomena, including sounds, light, heat, temperature, and electromagnetic noise.
Laput says the synthetic sensors can monitor the state of a device, while even more advanced sensors can deduce human activity. Plugging the units into a regular power socket makes batteries or special wiring unnecessary, although each room will likely require its own sensor platform.
The researchers presented their "Synthetic Sensors" project last week at the ACM Conference on Human Factors in Computing Systems (CHI 2017) in Denver, CO.
From Carnegie Mellon News (PA)
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