Assert AI's AI Analysis for Mumbai Suburban Railway Passenger Flow and Evacuation Study

Assert AI, a computer vision and video analytics company, has confirmed its role in conducting the CCTV-based artificial intelligence analysis that supported a major passenger flow and evacuation study covering Mumbai's suburban railway network.

The study, recently reported by The Times of India, assessed passenger movement and evacuation times across 49 stations on the Central and Western Railway networks. Its recommendations include wider staircases and foot overbridges, additional lifts and escalators, dedicated emergency exit corridors, better barrier-free access, multilingual directional signage and stronger CCTV coverage.

As part of the wider study undertaken for Mumbai Railway Vikas Corporation, Assert AI applied computer vision models to existing CCTV footage collected from the railway stations. The technology transformed extensive video recordings into structured information on passenger footfall, movement patterns, congestion points and the use of station entry, exit and platform areas.

AI Analysis Across 49 Railway Stations

The exercise covered 29 Central Railway stations and 20 Western Railway stations. Approximately 70 terabytes of CCTV footage was analysed, including video from 319 entry and exit cameras and 352 platform cameras. The study used 24-hour footage collected over five weekdays at every station, providing a substantial dataset for examining passenger movement under different operating conditions.

The AI analysis helped quantify:

Passenger footfall at different station locations
Peak-hour crowd density
Passenger entry and exit movement
Queue formation and congestion
Time spent by passengers in specific areas
Frequently used movement paths
Potential surveillance blind spots
Passenger distribution near staircases, platforms, lifts and escalators

The resulting data supported pedestrian flow simulations that examined evacuation performance under different passenger-load and infrastructure scenarios.

Supporting Evidence-Led Infrastructure Planning

According to the study findings reported by The Times of India, proposed engineering interventions could significantly reduce evacuation times at several stations. At Santacruz, the projected evacuation time could decrease from 12.07 minutes to 7.36 minutes. The estimated evacuation times at Borivali and Andheri could fall to 5.40 minutes and 5.26 minutes respectively after the proposed improvements.

The analysis also identified surveillance blind spots near platform ends at certain stations. Such areas could affect visibility during an emergency and increase the possibility of unauthorised track access. Strengthening CCTV coverage was therefore included among the study's recommendations.

Other recommendations included additional foot overbridges, wider staircases, more lifts and escalators, improved station lighting, dedicated emergency evacuation corridors and clearer multilingual signage.

"The objective of the AI analysis was to convert a very large volume of CCTV footage into measurable passenger movement intelligence," said Nitin Jain, Co-Founder of Assert AI. "Computer vision made it possible to study how passengers entered, exited and moved through station spaces at scale. This information can help planners evaluate proposed layouts and prioritise infrastructure interventions using evidence rather than relying only on manual observation."

Planning Exercise Focused On Future Requirements

Mumbai Railway Vikas Corporation has clarified that the findings form part of a forward-looking planning exercise based on mathematical simulations. They should not be interpreted as evidence that the stations are unsafe during normal operations. Existing layouts, proposed designs and infrastructure projects already under implementation must also be considered while reviewing the evacuation estimates.

Several improvement projects are already underway at high-footfall stations, including new and widened foot overbridges, elevated decks, wider staircases, additional escalators and lifts, and improved station access.

The project demonstrates how existing CCTV infrastructure can be used for more than surveillance. When combined with AI-based video analytics, recorded footage can provide quantitative insights for passenger flow planning, infrastructure design, accessibility and emergency preparedness.

Assert AI Pvt Ltd
Kanakia Zillion
A-303, Bandra Kurla Complex
Kurla, Mumbai

Assert AI develops computer vision and AI-powered video analytics solutions that convert video feeds into operational intelligence. Its technology can work with existing CCTV infrastructure to analyse movement, occupancy, queues and other visual events across complex environments. In the Mumbai railway study, the company's AI analysis supported the transition from labour-intensive manual passenger counting to scalable, data-driven assessment.

This release was published on openPR.