Machine Learning Container Recognition at Port Terminals
We developed an AI-powered system that optimizes container tracking and positioning at busy port terminals. The system uses a combination of computer vision and virtual mapping to track containers in real-time and assign optimal retrieval paths.
Computer vision algorithms for container tracking
Virtual mapping of dockyard layout for container location tracking
Real-time container tracking with over 90% accuracy
Challenge
Traditional container tracking methods were unreliable, especially in poor weather or lighting conditions, leading to inefficiencies and misrouted trucks at the port terminals.
Solution
Our system integrates computer vision with virtual mapping to provide real-time tracking of containers. The AI solution identifies container locations and optimizes retrieval paths, even in challenging conditions like low visibility.
Results
The system reduced container retrieval times by 8% and decreased misrouted trucks by 12%, enhancing terminal efficiency and increasing overall throughput.
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