Non-Intrusive Predictive System for Lift

I&T Solution Non-Intrusive Predictive System for Lift
(REF : S-0790)
Trial Project
Solution Feature
  • Install non-intrusive Fiber Bragg Grating (FBG) sensors to monitor equipment such as motor, steel rope
  • Install non-intrusive remote sensors to monitor the power quality of the equipment and vibration-based condition
  • No configuration for connecting internet directly via cellular network, flexible and easy hardware installation
  • User can access the dashboard to get current status of lifts from anywhere
  • Use AI Supercomputer with 4 Tesla V100 Tensor Cores for deep learning to analyze the time-series data and delta change to classify any abnormal behavior in the data
Trial Application and Expected Outcome
  • Place the sensors to the equipment and related devices such as motor, brake, safety circuit and door
  • Send out all parameters and data directly to the Cloud via cellular network, system can show historical and current status on Dashboard of PC/Mobile
  • Captured dataset will be analyzed using AI Supercomputer for deep learning algorithm to build a normal lift operation model
  • The model will be used to predict the coming real-time data and classify the operational status of lift
Info on I&T Solution Provider
Solution Provider:Pong Yuen Holdings Limited
Address:Units 1312-1313, 13/F., Building 19W, 19 Science Park West Avenue, Hong Kong Science Park, New Territories, Hong Kong
Contact Person:Tony Choy
Tel: 23658810

For details of the above I&T solution, please contact the I&T solution provider.