| I&T Solution |
AI Hauling Rope Condition Monitoring System
(REF: S-1269) |
| Trial Project |
|
| 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
|
| 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
|
| Additional Solution Information |
hampen_tram_cable_monitor.pdf
|
| 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 |
| Position | : | CEO | | Tel | : | 91863684 | | Email | : |
fchow@hampentech.com | | Webpage | : | www.hampentech.com |
|
