HawkEyes is real-time intelligence for physical spaces. It turns ordinary CCTV networks into a single, coherent system that understands movement, behavior, and intent across an entire facility.

Instead of isolated video feeds watched by tired human eyes, HawkEyes builds a living 3D view of a site and continuously reasons over what’s happening inside it. It doesn’t just monitor. It correlates, learns, and flags risks early — when prevention is still possible!

The web application is built with Next.js focusing on clarity and speed under pressure.

At the core is a streaming-first architecture. Confluent Cloud acts as the backbone, ingesting raw video frames and structured metadata at scale. Apache Flink processes streams with sub-second latency, enriching frames with spatial and temporal context.

On the intelligence side, Google Cloud Vertex AI powers detection and behavior analysis. Vision models handle object detection on every frame, while Gemini (used as a judge model in the loop) helps classify risk levels and anomalies. Structured outputs are stored in BigQuery for fast analytics and Google Cloud Storage for long-term history.

1. Clone the repository including submodules:

   git clone --recursive <repository-url>

2. Navigate to the project directory:

   cd HawkEyes/hawkeyes

3. Install dependencies:

   pnpm install

4. Set up the infrastructure using Docker:

   docker-compose up -d

5. Generate the Prisma client:

   npx prisma generate

1. Start the development server for the frontend:

   pnpm dev

2. In a separate terminal, start the backend service:

   cd backend
   pnpm dev

3. Access the application at http://localhost:3000.

Licensed under the Apache License 2.0.