An intelligent analytics platform for monitoring and predicting container movements inside port terminals and interfacing logistics networks. It ingests real-time container events through MQTT, classifies flows into Import, Export, and Transshipment operations, and predicts container dwell times. The platform includes an innovative anomaly detection index based on Algebraic Topology, developed by the team, to identify disruptions and emerging operational risks worldwide. Integrated with a Control Tower, it provides interactive visualizations, real-time situational awareness, predictive insights, and early-warning capabilities to support data-driven operational and strategic decisions.
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Main Gain(s): Improved operational visibility through real-time monitoring of container movements and disruptions.
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Use Case(s): …
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Start TRL: 2 - (evidences)
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Final TRL: 6 - (evidences)
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Main Contributions: (theoretics) E. Rocha, M. Antunes; (implementation) E. Rocha, A. Brochado, M. Antunes; (integration) A. Brochado
Main Features
- Real-time ingestion of container events through MQTT and other data integration mechanisms.
- Automatic classification of container flows into Import, Export, and Transshipment operations.
- Container dwell-time prediction using advanced machine learning and predictive analytics models.
- Innovative anomaly detection index based on Algebraic Topology to identify disruptions and abnormal operational patterns.
- Global disruption monitoring and early-warning capabilities across logistics and maritime-port networks.
- Interactive Control Tower integration for the real-time flow visualization.
Videos
| Container Terminal Simulation Tool (demonstration of human configurations and KPI visualization without real-time data) |