Delhi Metro Rail Corporation is integrating advanced Artificial Intelligence to modernize urban transit across the national capital. AI-driven systems are strengthening safety, improving efficiency, and enhancing passenger experience across the metro network. These initiatives reflect DMRC’s vision of building a secure, efficient, and technology-driven public transport system.

Introduction: 

In a significant stride toward smart urban mobility, the Delhi Metro Rail Corporation (DMRC) is actively leveraging Artificial Intelligence (AI) to enhance operational efficiency, passenger safety, system reliability, and overall service quality. These initiatives are currently being showcased at the AI Impact Summit at Bharat Mandapam, where Union Minister Manohar Lal Khattar visited DMRC’s stall and appreciated its forward-looking AI adoption.

DMRC’s AI roadmap covers multiple domains including passenger interaction, complaint redressal, infrastructure monitoring, predictive maintenance, and train safety systems — reflecting a comprehensive digital modernization strategy.

AI-Powered Passenger Assistance – Ask CHETNA:

One of the flagship innovations is CHETNA (Chatbot for Efficient Travel & Navigation Assistance) — a conversational Agentic AI system built on a BharatGPT-powered stack with Sovereign AI architecture.

Key Features of CHETNA:

This secure, India-hosted AI solution ensures seamless passenger engagement while maintaining data sovereignty and privacy. By providing instant, accurate responses, CHETNA significantly reduces dependency on manual helpdesks and enhances commuter convenience.

AI-Enabled Complaint Management System:

As part of its digital transformation drive, DMRC has introduced a modern Complaint Management System, now being upgraded to an Agentic AI-based framework.

Phase 1: Automation of Written Complaints

Phase 2: AI Voice Bot on Helpline 155370

This hybrid AI-human approach ensures efficiency without compromising on personalized service.

AI Monitoring of Overhead Wire Health:

Maintaining overhead equipment (OHE) is critical for uninterrupted metro services. DMRC has deployed advanced AI-based monitoring systems to ensure real-time diagnostics.

Pantograph Collision Detection System (PCDS):

Operational on:

The system uses accelerometers and drop-off sensors installed on train pantographs to continuously monitor contact with overhead wires. It identifies:

AI Video Analytics for OHE:

Implemented on:

AI-driven image analysis scans live video feeds to detect anomalies in the overhead wire network, enabling preventive interventions before faults escalate.

Strengthening Train and Track Safety:

DMRC has also integrated AI technologies to ensure optimal train health and operational safety.

Automatic Wheel Profile Monitoring System:

Automatic Axle Bearing Temperature Monitoring:

These systems enable real-time health assessment of rolling stock without disrupting operations.

Predictive Maintenance for Track Circuits:

On Green Line (Line 5) and Violet Line (Line 6), DMRC has introduced AI-based predictive maintenance systems for track circuits.

Expected Benefits:

Predictive analytics allows DMRC to identify potential failures before they occur, shifting from reactive to preventive maintenance — a major leap in metro system management.

Future Roadmap: Expanding AI Capabilities:

Looking ahead, DMRC plans to deploy more cutting-edge AI technologies across its network. The corporation is also focusing on:

These initiatives aim to position DMRC as a model for AI-driven public transportation systems in India.

Conclusion:

With AI embedded across passenger services, infrastructure monitoring, and predictive maintenance, the Delhi Metro Rail Corporation is redefining urban transit efficiency. By combining sovereign AI architecture with operational innovation, DMRC is building a safer, smarter, and more reliable metro network, setting a benchmark for future-ready public transportation systems in India.

Source: DMRC – Press Release | Image Credit (representational): DMRC

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