| I&T Solution |
AI Analysis on Traffic Data for Traffic Prediction and Management
(REF : S-1381)
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| Trial Project |
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| Solution Feature |
- Data collection on vehicle count and speed in real-time through LiDAR & Video camera
- Traffic prediction model development through temporal and spatial analysis, integrated external data
- Prediction of traffic congestion up to 30 minutes ahead
- Categorization of congestion into low, medium, and high
- Feedback loop for continuous model improvement
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| Trial Application and Expected Outcome |
- Install LiDAR sensors and cameras on a selected highway segment in Hong Kong. Collect real-time LiDAR and video data for congestion prediction. Evaluate the system's accuracy in predicting congestion levels based on combined LiDAR and video analytics.
- Collect data during a major event or a public holiday to analyse congestion patterns before, during, and after the event.
- Conduct real-time predictions and compare them with actual congestion levels. Measure the system's accuracy, precision, and recall in predicting congestion within the 30-minute timeframe.
- Deploy the system in an area affected by a temporary road closure. Predict congestion levels during the closure period and compare them with observed congestion.
- Refine the model with improved congestion judgement criteria.
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| Additional Solution Information |
AI Analysis on traffic data for traffic prediction.pdf
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| Info on I&T Solution Provider |
| Solution Provider | : | Kodifly Limited |
| Address | : | Unit 661, 6/F, Building 19W, No. 19 Science Park West Avenue, Hong Kong Science Park, Pak Shek Kok, N.T., Hong Kong |
| Contact Person | : | Mr Henry WONG |
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Position | : | CEO
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Tel | : |
6159 3979
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Email | : |
henry@kodifly.com
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Webpage | : |
https://www.kodifly.com
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