AI watching system for factory workers
Labor environment watching Solution by AI picture Analysis
Finding wrinkled or lay down labor due to fall-down or illness. Finding suspicious act such as unauthorized entry or work interruption
  • Posture identification (Supervised Learning, Inhouse Teaching data is used) Inform detected attitudes not occurred in usual work. Detected cases : Posture of fall down or crouch down.
  • Detection of abnormality in position, posture, number of workers and moving area. Entry to backside of manufacturing line, higher or lower moving speed of workers, Detection of dollies or containers left out working areas.
  • Detection of abnormality in unsupervised learning out of frequent operations. By learning patterns of stored data of more than months one can use pre-defined posture types and coordinate values for detection of new data as abnormality.
  • Defining notification rules. Defining rules for each abnormality makes immediate notification of such abnormality One can use appropriate communication channels such as email, LINE, SMS and smartphone apps for each notification.
  • Data Accumulations Data for all abnormalities including predefined HIARIHATTO : scary incident nearly missed.
This website uses cookies to provide you with a better user experience. By using our site you agree to the use of cookies as described by our cookie policy. If you do not want to accept all cookies from our website, please see our cookie policy on how to modify the types of cookies that are accepted by your browser client.