SAFETY FIRST. Police guide visitors at Tiruvannamalai during Karthigai Deepam festival | Photo Credit: VENKATACHALAPATHY C

Each year, the Karthigai Deepam festival at the Arunachaleswarar temple draws millions of pilgrims to Tiruvannamalai, Tamil Nadu, over a very short time period. On December 3, 2025, as the town prepared for peak inflows, authorities deployed a technology-supported surveillance and decision-assistance system to augment traditional policing and traffic management.

Active watch

At the centre of the technology deployment was an AI-enabled video analytics platform designed for large public gatherings. The system was implemented by Vehant Technologies, with Synergy Telematics as the master system integrator. Approximately 750 analytical points were distributed across key zones — the inner temple complex, surrounding arterial roads, the four main gopurams and the ‘Girivalam path’ (circumambulation of Arunachala hill).

These points drew from live feeds on cameras already installed or temporarily commissioned for the event. The platform functioned as a real-time aggregation layer, synthesising inputs from multiple locations into a consolidated operational view for the authorities. By providing this overview, the system enabled a transition from passive observation to active situational management.

Timely alerts

A core capability of the system was real-time crowd estimation across defined zones, such as entry points, queue corridors and congregation areas. Using video analytics, the software generated live occupancy estimates and compared them against predefined safety thresholds set by local authorities who are familiar with the site and historical crowd behaviour.

When live estimates approached or crossed these limits, alerts were triggered at the central command-and-control room (CCR), enabling officials to regulate inflow, temporarily divert foot traffic, open additional pathways or redeploy personnel before congestion escalated.

Girivalam path

The 14-km Girivalam path presents a distinct challenge due to its multiple access points, and the continuous movement of pilgrims. The platform provided a consolidated dashboard that visualised crowd concentration and flow trends along the different segments of the route.

In parallel, AI-assisted vehicle monitoring was used on approach roads and parking areas. In the absence of a centralised public parking facility, traffic management relied on tracking of vehicle inflow and outflow at multiple private parking zones.

Automated number plate recognition and virtual zoning allowed authorities to monitor capacity utilisation and respond when parking areas neared saturation. Alerts enabled traffic to be diverted proactively, reducing secondary congestion in pedestrian-heavy zones.

Behavioural cues

In addition to density monitoring, the system incorporated rule-based behavioural analytics to enforce crowd discipline. These included detection of barrier jumping and counter-flow movement in restricted or one-way corridors. Virtual zones and directional rules were defined in advance by the planners.

When live video feeds indicated a violation of these rules, alerts were issued to on-ground teams. This allowed security personnel to intervene early, before localised disruptions escalated into bottlenecks. Such capabilities were most relevant in high-pressure moments near darshan access points.

Command centre

All system outputs converged at the CCR, located within the temple premises. The facility was staffed by police personnel, including one Assistant Superintendent of Police, two sub-inspectors and five constables operating in eight-hour shifts. These teams were responsible for interpreting alerts, coordinating responses and maintaining communication with units across the town.

The platform interface prioritised clarity over automation, presenting live estimates, alerts and visual feeds to assist human operators. Decisions remained firmly with officials, supported by a continuously updated operational picture. According to those involved in the deployment, the primary value of the system lay in providing advance visibility of emerging pressure points to facilitate preventive action.

For administrators facing rising crowd densities and constrained manpower, such systems represent a pragmatic evolution in public safety strategy.

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Published on January 26, 2026