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