Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
One of Asia's largest transit networks carries more than seven million daily commuters across 395 kilometers of track and 289 stations in the Delhi-NCR region.
Critical data was trapped in fragmented systems, forcing teams to rely on manual monitoring and reactive maintenance for assets ranging from rolling...
“We are using predictive maintenance for track, signalling gears, bearings of rolling stock, lifts, and escalators. Additionally, the Passenger Information Display System (PIDS) provides real-time updates, and the Communication-Based Train Control (CBTC) system on the magenta and pink lines improves train automation and safety. These projects collectively enhance efficiency, sustainability, and user convenience.”
Public rail transit network for Delhi and its surrounding satellite cities.
Helped DMRC build a Data Center of Excellence (DCoE) on Google Cloud.
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