DMRC AI-driven innovations bring CHETNA, AI complaints, and OHE checks

DMRC AI-driven innovations are being rolled out to modernize urban transit across the national capital. Delhi Metro Rail Corporation says Artificial Intelligence will support safety, efficiency, reliability, and a better passenger experience across the metro network, as outlined by Delhi Metro Rail Corporation (DMRC).

Meanwhile, DMRC is showcasing these upgrades at the AI Impact Summit at Bharat Mandapam. During the event, Union Minister Manohar Lal Khattar visited DMRC’s stall and acknowledged the operator’s direction on AI adoption, as noted by the Press Information Bureau (PIB). DMRC’s roadmap spans passenger interaction, complaint redressal, infrastructure monitoring, predictive maintenance, and train safety systems.

DMRC AI-driven innovations for passenger interaction with CHETNA

A major passenger-facing tool is CHETNA (Chatbot for Efficient Travel & Navigation Assistance). DMRC describes it as a conversational Agentic AI system built on a BharatGPT-powered stack with a Sovereign AI architecture. Available on web and mobile platforms, CHETNA supports interactive journey planning, fare calculation and route guidance, real-time service updates, and ticket booking assistance.

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Also, DMRC says this secure, India-hosted setup is designed to maintain data sovereignty and privacy while delivering quick, accurate responses. Still, the chatbot is positioned to reduce dependence on manual helpdesks and improve commuter convenience.

Agentic AI complaint redressal and the 155370 voice bot

As part of its digital transformation drive, DMRC is upgrading its Complaint Management System into an Agentic AI-based framework. Separately, in Phase 1, written complaints are handled through AI-enabled categorization and routing. DMRC says this reduces Average Handling Time (AHT), improves transparency in workflow management, and speeds up grievance resolution.

At the same time, Phase 2 adds an AI voice bot on helpline 155370. The system is intended to use real-time intent recognition to register complaints automatically, with seamless escalation to human operators for complex cases. DMRC presents this as a hybrid AI-human approach that improves efficiency without losing personalized service where it is needed.

AI monitoring of overhead wire health and safety systems by line

Maintaining overhead equipment (OHE) is central to uninterrupted metro operations, and DMRC has deployed AI-based monitoring for overhead wire health. The Pantograph Collision Detection System (PCDS) is operational on the Red Line (Line 1), Yellow Line (Line 2), and Blue Line (Line 3/4). Using accelerometers and drop-off sensors installed on train pantographs, the system continuously checks contact with overhead wires. It flags risks such as wire misalignment, hard contact points, and potential mechanical failures.

In addition, AI video analytics for OHE has been implemented on the Pink Line (Line 7) and Magenta Line (Line 8). Here, AI-driven image analysis scans live video feeds to detect anomalies in the overhead wire network so preventive interventions can take place before faults escalate.

DMRC has also integrated AI tools to strengthen train and track safety. An Automatic Wheel Profile Monitoring System is installed on the Pink Line (Line 7), using high-precision laser sensors to scan wheels while trains are in motion and detect wear and deformation early. Automatic axle bearing temperature monitoring has been deployed on the Pink Line (Line 7) and Magenta Line (Line 8) to help prevent overheating-related failures and enhance passenger safety through real-time health assessment without disrupting operations.

On the track side, DMRC has introduced predictive maintenance for track circuits on the Green Line (Line 5) and Violet Line (Line 6). The expected benefits include fewer train delays, reduced emergency on-track interventions, optimized manpower deployment, enhanced service reliability, and safer, smoother operations. Predictive analytics is intended to help identify potential failures before they occur, supporting a shift from reactive responses to preventive maintenance.

Looking ahead, DMRC says it plans to expand AI capabilities across its network, including collaborations with AI domain experts, capacity building through workforce training modules, and strengthening indigenous, sovereign AI infrastructure, as reported by Rail Analysis. With AI embedded in passenger services, infrastructure monitoring, and predictive maintenance, Delhi Metro Rail Corporation positions these initiatives as steps toward a safer, smarter, and more reliable metro system in India.

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