A Japanese technology company wants to take the guesswork out of proper hand washing technique with a new sink-mounted surveillance system that will flag people for rushing or not using enough soap. Called'Actlyzer,' the AI-driven'hand wash movement recognition' system was developed by Fujitsu Laboratories and is being targeted for use in the Japanese food services industry, where employee cleanliness inspections are common. Fujitsu believes the'Actlyzer' system could also be used in hospitals, schools, hotels, stadiums, and any other public venue where large numbers of people might share a restroom. 'Actlyzer' is a new hand washing surveillance technology, that will evaluate whether a person is scrubbing properly and has used enough soap As the COVID-19 pandemic has brought new attention to safe hand washing practices, the company says'Actlyzer' could be an important part of a larger public safety campaign to lessen the spread of disease. 'Hand-washing will become even more essential in the days and months to come,' a Fujitsu spokesperson told The Asahi Shimbun.

Fujitsu Laboratories Ltd. and Fujitsu Research and Development Center Co., Ltd. have innovated an AI technology for video-based behavioral analysis. Dubbed "Actlyzer", the tech can recognize a variety of subtle and complex human activities without relying on large amounts of training data. Deep learning technologies conventionally demand large amounts of video data for training systems to recognize individual behaviors, and video data must be collected from scratch in order to add each new behavior. This time-consuming process means that it can often take several months to introduce functional AI into the field. Taking advantage of the fact that human behaviors generally consist of a combination of basic movements and actions, (e.g.

Fujitsu has developed a new artificial intelligence-based method of performing behavioral analysis on video footage, which it says can recognize a range of subtle and complex human activities without large amounts of training data, according to a company announcement. The new "Actlyzer" technology was developed by Fujitsu Laboratories and the Fujitsu Research and Development Center, and combines about 100 basic actions it is pretrained for modularly to identify more complex behaviors, such as acting suspiciously or considering a purchase. In contrast, Fujitsu says, deep learning technologies typically rely on huge amounts of video to train the recognition of individual behaviors, which means they take several months to be introduced in the field. The systems accuracy for recognizing the 100 basic actions is 90 percent or higher on average, according to Fujitsu. Suggested potential uses for the technology include automatic detection of suspicious activity, product interest surveys based on recognized purchase behavior, and training applications by comparing the skills of workers with different levels of experience in factories.