🔒 Smart Surveillance System

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🧠 Overview

Smart Surveillance System is a real-time AI-powered monitoring application built using YOLOv8.
It can detect and alert for multiple emergency situations such as fire, smoke, and accidents, making CCTV surveillance systems proactive instead of reactive.

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🚀 Features

• 🎥 Real-time Video Analysis — Runs object detection on live camera feeds or uploaded videos.
• 🔥 Fire Detection Module — Accurately identifies fire incidents using a custom-trained YOLOv8 model.
• ☁️ Multi-class Emergency Detection (Upcoming) — Extendable to detect smoke, accidents, and other hazards.
• 🌐 Web Dashboard —
  • Upload or stream video feeds
  • View live detection results
  • Visualize event logs & statistics

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🧩 Dataset

For the Fire Detection Module, we used a custom dataset from Roboflow Universe:

📂 Fire Dataset for YOLOv8 (by SmartCCTV AI)

• Dataset Type: Object Detection
• Format: YOLOv8 (TXT + Images)
• Classes: fire
• Source: Curated fire imagery from diverse environments

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🏗️ Tech Stack

Component	Technology
Model	YOLOv8 (Ultralytics)
Language	Python
Backend / Web App	Flask
Computer Vision	OpenCV
Data Tools	NumPy, Pandas
Visualization	Matplotlib, Roboflow

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⚙️ Installation & Setup

1. Clone the repository:

   git clone https://github.com/<your-username>/smart-surveillance-system.git
   cd smart-surveillance-system

   Create virtual environment.

2. Install dependencies:

   cd backend
   pip install -r requirements.txt

3. Run the application:

   python app.py

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🪪 License

This project is licensed under the MIT License - see the LICENSE file for details.