Surveillance and Security System

This project is an enhanced surveillance system that utilizes React, Django, and Machine Learning to monitor a geographic area for unusual or suspicious behavior. The system quickly detects and alerts authorities about potential threats, enabling a swift and coordinated response.

Features

• Advanced detection algorithms for real-time monitoring and identification of suspicious activities
• Instant notifications via WhatsApp or other communication channels for quick decision-making
• User-friendly React interface for easy interaction and monitoring
• Django backend for secure data storage and management
• Machine learning capabilities for continuous improvement and adaptation

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

• Python 3.x
• Node.js and npm
• Django
• React
• Machine learning libraries (e.g. scikit-learn, TensorFlow, etc.)

Installing

1. Clone the repository:

git clone https://github.com/Shanty34/WatchGuard.git

2. Create a virtual environment and activate it:

python -m venv venv
source venv/bin/activate (for Linux/Mac)
venv\Scripts\activate (for Windows)

3. Install the dependencies:

pip install -r requirements.txt
npm install

4. Run the Django server:

python manage.py runserver

5. Start the React development server:

npm start

6. Access the system at http://localhost:3000

Built With

• React - Frontend framework
• Django - Backend framework
• scikit-learn - Machine learning library
• TensorFlow - Machine learning library

Authors

• Azeem Idrisi
• Mridul Tiwari
• Shantanu Pant

See also the list of contributors who participated in this project.

License

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