CCTV Intelligence

Prototype for a camera monitoring system with a Go backend, WebSocket updates, and a small browser dashboard.

The repository is structured to keep camera ingestion, detection, queueing, encryption, and frontend display separate. It is useful as a starting point for real-time video processing work.

Features

• Go backend with HTTP and WebSocket routes
• Camera feed abstraction for RTSP/IP camera sources
• Placeholder detection layer for face/object recognition
• Frontend dashboard for live updates
• Docker setup with Redis and PostgreSQL
• Utility package for logging, benchmarking, and encryption work

Stack

• Go
• WebSockets
• PostgreSQL
• Redis
• Docker Compose
• HTML, CSS, JavaScript

Project Structure

.
├── backend/
│   ├── camera.go
│   ├── detector.go
│   ├── embeddings.go
│   ├── queue.go
│   ├── websocket.go
│   └── utils/
├── docker/
│   ├── Dockerfile
│   └── docker-compose.yml
├── frontend/
├── go.mod
└── README.md

Run With Docker

cp .env.example .env
docker compose -f docker/docker-compose.yml up --build

Open:

http://localhost:8080

Local Development

go run ./backend

By default the app uses a local webcam source:

CAMERA_URL=0

For an IP camera, set CAMERA_URL in .env or your shell.

Notes

• Real camera processing with GoCV requires OpenCV and GoCV installed on the host or inside the container.
• The current detection layer is intentionally stubbed so the project can be extended step by step.
• Do not commit real camera URLs, usernames, passwords, or encryption keys.

Roadmap

• Connect a real RTSP camera stream through GoCV.
• Add frame-level detection and event publishing.
• Store detection metadata without saving raw camera frames.
• Add dashboard filters for camera, time range, and event type.