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CASE STUDY / Data Engineering · AI & Data Science
Regional AI Smart Transportation Data Centre
Smart Mobility & Public TransportLed development, integration, and operation of an AI-enabled transportation data platform supporting multimodal mobility analytics, governance, and decision-making.
Delivery Details
This project integrated regional multimodal transport data into an operational AI-enabled smart transportation data centre. The data-engineering work covered source and interface discovery, batch and real-time integration, quality controls, master-data definitions, permissions, and governance; the data-science work covered mobility behavior analysis, demand insight, anomaly identification, and decision-support applications. Operating processes, a data catalogue, and analytical services enabled diverse mobility data to be managed consistently and continuously converted into planning and operational insight.
Industry Context
Regional mobility combines bus, rail, road, and other services whose sources, frequencies, and spatial granularity differ substantially. AI and decision support require reliable integration, governance, and operations before multimodal data can become demand, movement, and anomaly insight.
Business Problem
Multimodal data was fragmented across sources and formats, preventing a consistent, sustainable regional view.
What I Built
Built platform and governance workflows to integrate mobility data and operationalize analytics.
Business Impact
Created a regional transport data foundation for mobility analysis, monitoring, and evidence-based decisions.
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