Device to save kids, pets in vehicles developed

Update: 2019-11-12 05:30 IST

Researchers from the University of Waterloo, Canada, have developed a new device that combines radar technology with Artificial Intelligence (AI) to detect unattended children or animals with a 100 percent accuracy.

Small enough to fit in the palm of a hand at just 3nm in diameter, the device is designed to be attached to a vehicle's rear-view mirror or mounted on the ceiling.

According to the researchers, it sends out radar signals that are reflected back by people, animals and objects in the vehicle. The built-in AI then analyses the reflected signals.

"Unlike cameras, this device preserves privacy and it doesn't have any blind spots because radar can penetrate seats, for instance, to determine if there is an infant in a rear-facing car seat," said study researcher George Shaker, a Professor at the University.

"This system is so affordable it could become standard equipment in all vehicles," he added.

Development of the wireless, disc-shaped sensor was funded in part by a major automotive parts manufacturer that is aiming to bring it to market by the end of 2020.

Analysis by the device determines the number of occupants and their locations in a vehicle.

That information could be used to set rates for ride-sharing services and toll roads, or to qualify vehicles for car-pool lanes.

Its primary purpose, however, is to detect when a child or pet has been accidentally or deliberately left behind, a scenario that can result in serious harm or death in extremely hot or cold weather, the study said.

In such cases, the system would prevent vehicle doors from locking and sound an alarm to alert the driver, passengers and other people in the area that there is a problem.

The low-power device, which runs on a vehicle's battery, distinguishes between living beings and inanimate objects by detecting subtle breathing movements.

Researchers were now also exploring the use of that capability to monitor the vital signs of drivers for indications of fatigue, distraction, impairment, illness or other issues.

The study was presented at the IEEE Sensors 2019 conference in Canada.

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