Indian Railways to Use AI for More Secure Operations

Overview

By incorporating Artificial Intelligence (AI) and Machine Learning (ML) technologies into its network, Indian Railways has made significant progress toward modernizing its operations. From sophisticated station surveillance to the detection of tampered wagon doors, these innovations tackle important safety, maintenance, and security issues.

The size and complexity of railway operations necessitate advanced digital technologies, with millions of passengers and thousands of freight trains traveling every day. Indian Railways hopes to improve passenger confidence and service quality while increasing operational reliability, optimizing asset management, and preventing accidents through the use of AI.

Key Developments in AI Deployment

AI for Freight Safety and Train Maintenance

The Locking Monitoring System “DRISHTI,” which is intended to identify unlocked or tampered doors on moving freight wagons, is a noteworthy endeavor. By automating inspections that were previously done by hand, an AI-based technology lowers human error and improves cargo security.

In order to automate rolling-stock diagnostics including axle temperature, hot bearings, and braking conditions, Indian Railways is also creating Machine Vision-Based Inspection Systems (MVIS). By detecting possible technical issues prior to malfunctions, these technologies guarantee predictive maintenance and lower operational risks.

AI-Powered Surveillance and Smart Stations

At important stations, Indian Railways is implementing video analytics and AI-enabled facial recognition cameras for passengers. By identifying suspicious activities and instantly notifying authorities via integrated command centers, these systems improve security.

To provide unified analytics across departments, centralized AI and ML-based decision-support tools are also being implemented. Evidence-based decision-making and improved coordination between railway zones will be made possible by these technologies.

Benefits and Challenges

Benefits of AI Integration

• Improved Safety: Accidents and derailments are decreased via automated fault identification.
• Operational Efficiency: Turnaround time is improved via quicker inspection and real-time monitoring.
• Cost Reduction: Predictive maintenance prolongs the life of assets and reduces repair expenses.
• Passenger Confidence: The rail system is more trustworthy thanks to smart surveillance and digital safety measures.

Challenges in Implementation

• Data Management: It’s still difficult to handle and integrate large amounts of sensor and image data.
• Skill Development: Training in AI tools, data analytics, and system management is necessary for railway employees.
• Cybersecurity and Privacy: Digital technologies pose ethical questions about data use and make users more vulnerable to cyberattacks.
• Infrastructure Diversity: There are logistical challenges in standardizing AI deployment across diverse terrains and legacy systems.

The Way Forward

Indian Railways must use a methodical, phased approach that consists of the following in order to fully utilize AI in railway operations:

• Institutional Coordination: Creating central frameworks for AI governance to facilitate departmental cooperation.
• Data Infrastructure Strengthening: Increasing IoT networks, sensors, and cloud systems to gather trustworthy real-time data.
• Workforce Training: Developing engineers’ and operators’ AI literacy for effective system management.
• Ethical Guidelines: Providing precise standards for data privacy, facial recognition, and AI monitoring.
• Public–Private Partnerships: Promoting innovation and cooperation in technology to expand pilot initiatives.

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About the Author: Jyoti Verma