| I&T Solution |
AI Hauling Rope Condition Monitoring System
(REF : S-1269)
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| Trial Project |
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| Solution Feature |
- Real-time monitoring of hauling rope with high-speed cameras
- Convolutional Neural Network (CNN) AI model trained to classify multiple types of rope conditions or abnormalities
- Mobile app notification to alert staffs
- Live view of cameras and detection logs on web-based management portal
- Handle different weather conditions
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| Trial Application and Expected Outcome |
- Install high speed cameras and lighting to capture different types of abnormalities, wear and tears/conditions of hauling cable
- Work with domain experts to identify and extract training images into different abnormality classes and start training CNN AI model
- Evaluate AI model performance and iterate with additional training data to make the AI model converge
- Apply AI model to real-time system and evaluate performance
- Additional rounds of model refinement training might be needed to create an AI model that can achieve high accuracy and low false positive rate
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| Additional Solution Information |
hampen_tram_cable_monitor.pdf
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| Info on I&T Solution Provider |
| Solution Provider | : | Hampen Technology Corporation Limited |
| Address | : | 907G, 9/F, Block B, Hong Kong Industrial Centre, 489 Castle Peak Road, Lai Chi Kok, Kowloon. |
| Contact Person | : | Felix Chow |
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Position | : | CEO
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Tel | : |
91863684
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Email | : |
fchow@hampentech.com
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Webpage | : |
www.hampentech.com
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