Panasonic announced that it has developed a technology for detecting and predicting a driver’s level of drowsiness.
The technology – which Panasonic says can help prevent drowsy driving – detects a driver’s shallow drowsiness at the initial state by measuring the driver’s states, captured by an in-vehicle camera, and processing these signals using artificial intelligence.
A person who feels drowsy shows various signs. For example, people will “have a drowsy facial expression,” or “blink in a specific way,” when becoming drowsy. Identifying these signs allows to detect the level of drowsiness.
Panasonic has developed technology for detecting people’s blinking features and facial expressions, etc. from photographed images, using image recognition technologies refined through the development of monitoring cameras and other systems.
The company has also compiled a database of various measurements on drowsiness and biological signals, and analyzed, from a physiological standpoint, the relationship between about 1,800 parameters related to blinking features and facial expressions, etc., and drowsiness that were extracted from the database. Based on the results of an analysis of drowsy expressions compiled during joint research with the Ohara Memorial Institute for Science of Labour, Panasonic has developed AI capable of estimating an individual’s drowsiness level.
Using measurement data from the in-vehicle environment, such as heat loss from the driver and illuminance, the technology can also predict changes in the driver’s drowsiness level. The technology also includes a thermal sensation monitoring function, which Panasonic says allows the driver to stay comfortably awake while driving.
Video is available.
Conventional drowsiness-detection systems have had difficulty in predicting transitions in drowsiness, and tend to use anti-hypnotic stimulant systems,alarm sounds and vibrations to wake up users, which can make them feel uncomfortable.
Panasonic says its technology, with 22 patents on file, is suitable for applications in human- and environment-monitoring systems not only for private and commercial vehicles, but also offices and educational institutions.