https://github.com/dearabhin/ai-surveillance-system
The AI Beach Surveillance System is designed to monitor public beaches and ensure safety by detecting people crossing predefined danger zones. It uses cutting-edge AI technology for real-time object detection and alerts the authorities when a person enters a restricted area, preventing potential accidents.
https://github.com/dearabhin/ai-surveillance-system
ai security surveillance
Last synced: 12 days ago
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The AI Beach Surveillance System is designed to monitor public beaches and ensure safety by detecting people crossing predefined danger zones. It uses cutting-edge AI technology for real-time object detection and alerts the authorities when a person enters a restricted area, preventing potential accidents.
- Host: GitHub
- URL: https://github.com/dearabhin/ai-surveillance-system
- Owner: dearabhin
- License: mit
- Created: 2024-11-17T05:33:08.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-01-20T04:14:17.000Z (9 months ago)
- Last Synced: 2025-06-04T13:29:07.359Z (5 months ago)
- Topics: ai, security, surveillance
- Language: Python
- Homepage: https://abhinkrishna.com
- Size: 16.6 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AI-Based Beach Surveillance System
## 🌊 Overview
The AI-Based Beach Surveillance System is designed to monitor public beaches using live video feeds and AI. The system ensures safety by detecting people crossing predefined boundaries (like a sea or danger zone) and sending real-time alerts to prevent potential dangers.
---
## ✨ Features
- **Real-Time Video Monitoring**: Tracks people on the beach and their proximity to the danger zones.
- **Boundary Detection**: Uses AI models to detect if people cross safety limits.
- **Alerts**: Automatically sends email alerts when a person enters the danger zone.
- **User Interface**: A simple web-based interface to start and stop monitoring.
---
## 🛠️ Technology Stack
- **Backend**: Python, Flask
- **Frontend**: HTML, CSS, JavaScript
- **AI Models**: YOLOv8 for object detection
- **Other Tools**: OpenCV for video processing, SMTP for sending alerts
---
## 🚀 Getting Started
### 1. Clone the Repository
```bash
git clone https://github.com/dearabhin/AI-Beach-Surveillance-System.git
cd AI-Beach-Surveillance-System
```
### 2. Install Dependencies
Ensure you have Python 3.8+ installed. Then, install the required Python packages:
```bash
pip install -r requirements.txt
```
### 3. Set Up Email Alerts
Update the `alert_system.py` file with your email credentials:
- `sender_email`: Your email address
- `receiver_email`: The email to send alerts
- `password`: Your email password (or app password if using Gmail)
### 4. Run the Application
Start the Flask server:
```bash
python src/app.py
```
Access the web app at `http://127.0.0.1:5000`.
---
## 📂 Project Structure
```
AI-Beach-Surveillance-System/
│
├── data/ # Training data for AI models
├── models/ # Pre-trained and fine-tuned models
├── src/ # Source code
│ ├── app/ # Flask application
│ │ ├── static/ # Frontend assets (CSS, JS, images)
│ │ ├── templates/ # HTML templates
│ │ ├── app.py # Main Flask app
│ │ ├── monitoring.py # Real-time monitoring logic
│ │ ├── detection.py # AI-based detection
│ │ ├── alert_system.py # Email alert system
│ │ └── utils.py # Helper functions
├── requirements.txt # Python dependencies
├── README.md # Project documentation
└── LICENSE # License file
```
---
## 🌟 How It Works
1. The system starts live monitoring using the `monitoring.py` script.
2. **Object Detection**: The YOLOv8 model detects people in the video feed.
3. **Boundary Monitoring**: The system tracks the position of detected people relative to the danger zone boundary.
4. **Alerts**: When someone crosses the boundary, the `alert_system.py` script sends an email alert.
---
## 📸 Screenshots
### Home Page
### Monitoring in Action
---
## 💻 Deployment
### Local Deployment
Follow the [Getting Started](#getting-started) steps to run the app locally.
### Cloud Deployment
You can deploy the application on platforms like:
- **Heroku**
- **AWS EC2**
- **Google Cloud Platform**
- **Microsoft Azure**
---
## 🛡️ License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
---
## 🙋♂️ Contributing
Contributions are welcome! Feel free to fork the repository and submit a pull request.
---
## 📧 Contact
For any queries or feedback, reach out to **abhinkrishna.com**.
---
## 🌍 Acknowledgments
Special thanks to:
- [YOLOv8](https://github.com/ultralytics/yolov8) for the powerful object detection model.
- OpenCV for real-time video processing.
- Flask for a lightweight backend framework.
```
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