Researchers at Cornell University have developed a single device that can track 17 types of appliances using vibrations.
The device, VibroSense, uses lasers to capture vibrations in walls, ceilings and floors and a deep learning network creates different signatures for each device.
"Recognizing home activities can help computers better understand human behaviors and needs, with the hope of developing a better human-machine interface," said Cheng Zhang, assistant professor of information science at Cornell. "In order to have a smart home at this point, you'd need each device to be smart, which is not realistic; or you'd need to install separate sensors on each device or in each area. Our system is the first that can monitor devices across different floors, in different rooms, using one single device."
Researchers created the sensor device to detect usage in two ways: First, to detect tiny vibrations using a laser Doppler vibrometer; and second to differentiate similar vibrations created by multiple devices by identifying the paths traveled by the vibrations from room to room.
The device was trained to distinguish between different activities and learning path signatures as well as distinct noises. VibroSense showed nearly 96% accuracy in identifying 17 different activities across five houses including dripping faucets, an exhaust fan, an electric kettle, a refrigerator and a range hood.
VibroSense could also distinguish between five different stages of appliance usage with an average accuracy of more than 97%.
Researchers said the device could be used to help homes monitor energy usage and potentially help reduce power consumption.
"Since our system can detect both the occurrence of an indoor event, as well as the time of an event, it could be used to estimate electricity and water-usage rates, and provide energy-saving advice for homeowners," Zhang said. "It could also prevent water and electrical waste, as well as electrical failures such as short circuits in home appliances."
The full research can be found in the journal Digital Library.
