Hello everyone,

I am working on a typical problem of real-time data analysis/datamining of an urban transport system where i have following information

- Data about how many vehicles are part of the transport system with their last known location always updated as GPS coordinates.

- Data about different routes the buses may travel with a list of stops, their zone and their GPS coordinates. Worth mentioning that a stop can be part of more than one routes where buses going to different destinations may share some stops with other buses.

- Data about the journeys that have been travelled and more specifically the journeys that are being travelled right now in real-time. This contains information about the routes, stops and then actual arrival and departures times being reported. It also contains information about planned start/end time of the journey (based on planning) and actual start and end time for the whole journey. It also contains planned arrival and departures time for each stop that is/will be travelled by the bus.

Having all that data available, I need little creative thinking to suggest what different scenarios or problems that can be addressed using analysis/mining of this data. Like congestion detection, different types of congestion, scenarios for delays and emergency situations, resource planning, rerouting - anything you can think of will be helpful. Please share your ideas.

Regards

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