The Gujarat Police are looking for technology solutions that can bring more than 80,000 CCTV cameras across the state onto a single surveillance network. The state police have announced what they describe as the country’s largest hackathon focused on CCTV integration and AI-based video analytics.
The initiative aims to develop a technology platform that can help law enforcement analyse video feeds in real time, identify people and vehicles of interest, and respond more quickly to potential incidents. The hackathon is being organised under the Gujarat Home Department and will bring together students, researchers, freelancers, startups and technology companies. The event is scheduled for September 10 and 11 at iHub Gujarat in Ahmedabad, with a total prize pool of ₹37 lakh.
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What does the Gujarat Police CCTV hackathon aim to achieve?
At the heart of the challenge is a straightforward problem: Gujarat has thousands of CCTV cameras operated by different departments and systems, but these networks do not currently function as one integrated surveillance platform.
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The Gujarat Police want participants to develop a system capable of connecting these disparate camera networks and turning them into a unified video management and analytics ecosystem.
The four main objectives are:
- Integrate different CCTV systems into a common platform.
- Cross-reference live video feeds with relevant government databases.
- Use AI to identify people, vehicles and events of interest.
- Generate real-time alerts to help police respond faster.
The proposed system will need to work across different types of infrastructure. According to the hackathon details, some departments currently use cloud-based storage, while others rely on locally hosted systems.
What technology is the hackathon looking for?
The challenge goes beyond simply bringing CCTV feeds onto one screen. Participants are expected to demonstrate how AI and video analytics can turn large volumes of surveillance footage into actionable information.
Key capabilities include real-time suspicious-activity detection, automatic number plate recognition (ANPR), vehicle tracking, watchlist matching and cross-camera searches. The system should also be able to follow the movement of a vehicle across multiple camera locations, maintain movement history and allow investigators to search recorded events.
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GIS visualisation is another important component. Participants will have to demonstrate how surveillance events and vehicle movements can be represented geographically, giving police a clearer picture of incidents unfolding across different locations.
How will the CCTV system be tested?
The technical evaluation will use approximately 50 geographically distributed and heterogeneous CCTV cameras. Participants will receive access to live feeds from around 50 cameras through the hackathon’s resources portal. They will then have to demonstrate their system against practical policing scenarios rather than relying only on a software presentation.
The evaluation will include tasks such as:
- Integrating multiple camera systems.
- Tracking a designated vehicle across different locations.
- Generating real-time alerts.
- Searching events across camera feeds.
- Displaying information through GIS-based visualisation.
- Creating a history of vehicle movements.
The approach is intended to test whether a proposed solution can handle the complexity of a large, distributed CCTV network.
Who can participate in the Gujarat Police hackathon?
The challenge is open to a broad range of technology innovators. Students, researchers, freelancers, startups and established companies can participate. This broad eligibility matters because the police are not limiting the challenge to established surveillance technology providers. Academic teams and smaller technology companies can also put forward solutions for large-scale public safety applications.
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Participants are required to submit a working prototype along with technical documentation and details of their system architecture.
What do participants need to submit?
The submission package includes several components to help the evaluation committee assess both the technology and its practical implementation.
Participants are required to provide:
- An unlisted YouTube video demonstrating their solution.
- A Google Drive or OneDrive link with viewer access enabled.
- A hosted platform URL and test credentials, where applicable.
- A GitHub or GitLab repository containing the source code or relevant components, where applicable. The evaluation will begin with common assessment criteria. Solutions that demonstrate useful capabilities beyond the mandatory requirements may receive additional consideration.
How to register for the Gujarat Police CCTV hackathon
Participants can register through the Sentinel Gujarat portal. Once registered, they can access technical resources and information needed to develop and test their solutions. The resources include live feeds from approximately 50 cameras located across different parts of Gujarat. These feeds are intended to give teams a realistic environment in which to test CCTV integration, video analytics and surveillance capabilities.
The final objective is not simply to build another CCTV dashboard. Gujarat Police are looking for a scalable system that can potentially connect a state-wide network of more than 80,000 cameras and make the resulting data more useful for policing.
If successful, the technology developed through the challenge could offer a model for how large, fragmented CCTV networks can be brought together with AI-based analytics and real-time monitoring.
Indrani Priyadarshini is a journalist and editorial professional specialising in technology, artificial intelligence, smart cities, green energy, and digital transformation. With over four years of experience in tech journalism and digital media, she is known for turning complex industry developments into clear, engaging, and insightful stories. Her expertise spans reporting, editorial strategy, digital publishing workflows, and in-depth coverage of emerging technologies shaping the future.
