| I&T Solution |
Fixture and Signboard Defect Detection
(REF: S-1647) |
| Trial Project |
|
| Solution Feature |
- Identify the roadside fixtures (both normal or defective) from street image
- Identify the 1st defective factor - deformation
- Identify the 2nd defective factor - corrosion
- Defective factor analysis
- Risk indicator consolidation
|
| Trial Application and Expected Outcome |
- Develop an AI model capable of detecting roadside fixtures based on visual analysis.
- Design and implement an edge-device system that collects and processes street-side visual data.
- Develop a UI to visualize the results and upload images for analysis.
- Demonstrate the accuracy and efficiency of the proposed AI-enabled system in real-world conditions.
- Assess the feasibility, scalability, and potential impact of deploying the system for further development.
|
| Additional Solution Information |
EMSD RoadsideREF W-0513.pdf
|
| Info on I&T Solution Provider |
| Solution Provider | : | Green AI Technology Limited | | Address | : | Unit B, 4/F, Yee Wah Ind.Bldg., 18 San On Street, Tuen Mun, Hong Kong | | Contact Person | : | Dennis Mak |
| Position | : | Chief Innovation Officer | | Tel | : | 96295360 | | Email | : |
dennis@greenaitech.com |
|
