Women Safety Analytics 🚨

Project Overview

Women Safety Analytics is a real-time threat detection platform aimed at enhancing the safety of women in public spaces. This platform leverages Artificial Intelligence (AI), Machine Learning (ML), and IoT technologies to monitor, detect, and alert users about potential threats. Additionally, it empowers communities to report unsafe areas and assists law enforcement in responding to incidents more quickly.

Features

• Real-Time Threat Detection: AI-driven detection of suspicious activities in public spaces.
• Emergency Alerts: Immediate alerts to law enforcement, guardians, and nearby users.
• Gesture-Based Emergency Triggers: Allows users to send an SOS alert with predefined gestures.
• GPS Tracking: Real-time location sharing and guidance to the nearest safe areas.
• Community Reporting: User-driven reports on unsafe locations for proactive safety.
• Predictive Crime Analytics: Analysis of past incidents to predict potential crime hotspots.

Android App Features

• Panic Alarm Activation: Notify contacts and nearby users instantly during emergencies.
• Safety Tips & Resources: Provides safety suggestions and directions to nearby safe areas.

Technology Stack

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript
• Mobile App: Android (Java/Kotlin)
• Machine Learning: AI models for anomaly detection and behavioral analysis
• Database: MySQL/PostgreSQL
• Cloud Services: AWS/Google Cloud (for real-time data processing and storage)

Installation and Setup

Prerequisites

• Python 3.x
• Flask
• MySQL/PostgreSQL (or any preferred database)
• Android Studio (for mobile app development)

Steps to run the project:

1. Clone the repository:

   git clone https://github.com/your-username/women-safety-analytics.git
   cd women-safety-analytics
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Set up the database and apply migrations:

   flask db init
   flask db migrate
   flask db upgrade
   

4. Start the Flask server:

   flask run
   

Usage

• Web Interface: Use the web application to view real-time surveillance data, crowd analytics, and safety hotspots.
• Mobile App: The Android app enables quick access to safety features, including panic alarms and real-time location tracking.

Contribution

Ronak Parmar and Team

License

This project is licensed under the MIT License.