Vibration device boosts the benefits of a smart home
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Researchers in the US have developed a device that can track 17 different household appliances using vibrations and they say could improve efficiency in the home.
Developed by researchers at Cornell University, 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.
“Recognising home activities can help computers better understand human behaviours and needs, with the hope of developing a better human-machine interface,” said Cheng Zhang, assistant professor of information science.
He added that in order to have a smart home at this point, users would need each device to be smart, which is not realistic; or homeowners would 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.”
In order to detect usage across an entire house, the researchers’ task was twofold: detect tiny vibrations using a laser Doppler vibrometer, and differentiate similar vibrations created by multiple devices by identifying the paths travelled by the vibrations from room to room.
The deep-learning network was trained to distinguish different activities, partly by learning path signatures – the distinctive path vibrations followed through the house – as well as their distinct noises.
According to the researchers, the device showed nearly 96 per cent accuracy in identifying 17 different activities – including dripping faucets, an exhaust fan, an electric kettle, a refrigerator, and a range hood – in five houses over two days. VibroSense could also distinguish five different stages of appliance usage with an average accuracy of more than 97 per cent.
The laser was pointed at an interior wall at the centre of a single-storey home, and at the ceiling in a two-storey house.
Zhang said the device is primarily useful in single-family houses because in buildings such as a block of flats it could pick up activities in neighbouring homes, presenting a potential privacy risk. “It would definitely require collaboration between researchers, industry practitioners, and government to make sure this was used for the right purposes,” he said.
Among other uses, the system could also help homes monitor energy usage and potentially help reduce 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.”
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