Gujarat Police has announced plans to integrate more than 80,000 CCTV cameras across the state into a single unified surveillance network, using the Gujarat Police Innovation Challenge 2026 — described as the country's largest hackathon focused on CCTV integration and AI-based video analytics — to source the technology solutions needed to make it happen.

What the Challenge Aims to Solve

The core problem Gujarat Police is trying to crack is fragmentation. The state's existing CCTV infrastructure spans multiple vendors, technologies, video management system platforms, and network architectures that currently cannot talk to each other. The challenge, announced on Monday, 17 August 2026, will task participants with building systems that bridge this divide — allowing disparate cameras to function as one cohesive network and giving police faster, more reliable access to surveillance data.

Participants will be required to develop AI-driven tools capable of identifying suspicious individuals, vehicles, and unusual activity patterns, while generating real-time alerts. Additional capabilities under evaluation include automatic number plate recognition, vehicle tracking, watchlist matching, and multi-camera search functions.

Structure of the Competition

The hackathon will run in two stages under the leadership of Director General of Police (DGP) G.S. Malik. The first stage — the Open Innovation Challenge — will have two categories: one open to students and small and medium-sized startups, and a second for larger startups and established technology companies. The six best-performing teams from this stage will advance to the finale, where they will demonstrate their solutions in a live production environment using real-world policing scenarios.

The competition carries total cash prizes of ₹37 lakh. The hackathon is expected to begin in September 2026, with participation details, eligibility criteria, and guidelines available through the official Sentinel Gujarat portal.

Institutional and Technology Partners

The initiative has technology partnership support from i-Hub Gujarat and knowledge partnership support from DA-IICT and the National Forensic Sciences University (NFSU). The involvement of academic and forensic science institutions signals an intent to ground the competition in practical, deployable policing applications rather than theoretical prototypes.

A distinctive feature of the challenge is that participants will test their AI applications using live CCTV feeds and real-world scenarios — raising the bar beyond lab-based demonstrations and placing a premium on systems that can perform under operational conditions.

Broader Context

The Gujarat initiative reflects a wider shift among Indian police forces toward AI-augmented surveillance as the volume of CCTV footage outpaces the capacity of human operators to review it. Rather than overhauling existing infrastructure — a costly and time-consuming undertaking — Gujarat Police's approach emphasises interoperability: building software layers that can work across the current patchwork of hardware already in the field.

This vendor-agnostic strategy, if successful, could offer a replicable model for other states grappling with similarly fragmented surveillance ecosystems. The results of the finale are expected to directly inform procurement and deployment decisions by the force.