A total of 750 trains run across a network of 8500 km in a day and generate real-time data at approximately 50 sensor platforms. With the help of structured streaming and Delta Lake, ARTC was able to analyze and store:
– Precise train location
– Weight of the train in real-time
– Train crossing time to the second level
– Train speed, temperature, sound frequency, and friction
– Train schedule lookups
Once all the IoT data has been pulled together from an IoT event hub, it is processed in real-time using structured streaming and stored in Delta Lake. To understand the train GPS location, API calls are then made per minute per train from the Lakehouse. API calls are made in real-time to another scheduling system to lookup customer info. Once the processed/enriched data is stored in Delta Lake, an API layer was also created on top of it to expose this data to all consumers.
The outcome: increased transparency on weight data as it is now made available to customers; we built a digital data ecosystem that now ARTC’s customers use to meet their KPIs/ planning; the ability to determine temporary speed restrictions across the network to improve train scheduling accuracy and also schedule network maintenance based on train schedules and speed.
Talk by: Deepak Sekar and Harsh Mishra
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