| I&T Solution |
AI-powered System that Uses Real-time Video Analytics to Detect Passenger Queues, Track Vehicle Arrival Patterns, and Measure Occupancy Levels at Transit Waiting Areas.
(REF: S-2048) |
| Trial Project |
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| Solution Feature |
- Uses multi-layered computer vision models to detect people, queues, vehicles, and movement patterns in real time.
- Employs segmentation and transformer-based detection to handle occlusion, dense crowds, and complex environments with high accuracy.
- Provides continuous occupancy measurement and automatically logs queue build-up, arrival timestamps, and peak-demand periods.
- Generates actionable insights by analysing patterns such as prolonged waiting times, route-specific congestion, and service gaps.
- Offers non-intrusive deployment through existing camera infrastructure, with edge/cloud processing and privacy-preserving video handling.
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| Trial Application and Expected Outcome |
- Install cameras at selected stops and configure virtual zones to begin automated queue and arrival-time monitoring under real operating conditions.
- Validate accuracy of people detection, queue length measurement, and vehicle time-stamping through comparison with manual observation samples.
- Assess system stability and scalability by running continuous monitoring across peak and off-peak periods.
- Analyse collected data to identify patterns of prolonged waiting and peak demand, demonstrating how AI insights improve planning.
- Evaluate operator response time improvements through real-time alerts for queue build-up or extended waiting durations.
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| Additional Solution Information |
HK EMSD Bus Monitoring.pdf
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| Info on I&T Solution Provider |
| Solution Provider | : | Tictag Hong Kong Ltd | | Address | : | 5/F, Building 5E, 5 Science Park East Avenue | | Contact Person | : | Kevin Quah Lian Shen |
| Position | : | CEO | | Tel | : | 97939073 | | Email | : |
kevin@tictag.io | | Webpage | : | www.tictag.io |
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