| I&T Solution |
Non-Intrusive Predictive System for Lift
(REF: S-0790) |
| Trial Project |
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| 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
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| 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
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| 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 |
| Position | : | Manager | | Tel | : | 23658810 | | Email | : |
tony.choy@pongyuen.com.hk | | Webpage | : | www.pongyuen.com.hk |
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