A Real-Time AI-Powered Solution for Safer Public Spaces
SafeAura is a cutting-edge solution designed to protect women from potential threats in public spaces using AI-driven real-time monitoring. By integrating seamlessly with existing CCTV infrastructure, our system proactively detects unsafe situations and alerts authorities, creating a safer world for women.
Built on powerful AI models, our solution analyzes live video feeds to detect threats, classify gender, and identify high-risk areas, giving law enforcement and security teams the tools they need to act before incidents escalate.
- 🔍 Real-Time Threat Detection: Identify unsafe situations like a lone woman in a risky area, surrounded by men, or SOS gestures.
- 💡 Gender Classification: AI models trained to detect and classify gender in real-time, providing context for situations.
- 📡 Hotspot Detection: Analyze data to find high-risk areas that need heightened security measures.
- 📲 Instant Alerts: Authorities are notified immediately with relevant footage and information for faster responses.
- 🌐 Seamless Integration: Works effortlessly with existing CCTV systems, making it easy to scale in cities or campuses.
Our solution is built using the latest and most efficient technologies:
- YOLO (You Only Look Once): For lightning-fast object and threat detection.
- OpenCV: For advanced image processing and video stream handling.
- Roboflow: For managing and annotating datasets, ensuring high-quality model training.
- LSTM (Long Short-Term Memory): To predict high-risk areas by analyzing historical patterns.
- Flask + Node.js: For backend processing, real-time alerts, and secure communication.
- React: For a clean, intuitive user interface that makes monitoring simple and actionable.
- Python & Pandas: For real-time data stream handling and processing.
- Video Input: Feeds from CCTV cameras are processed in real-time.
- AI Analysis: Using YOLO and OpenCV, the system detects people, classifies gender, and recognizes unsafe scenarios.
- Hotspot Prediction: With LSTM, our system analyzes patterns to predict areas prone to risk.
- Alerts & Insights: When a threat is detected, authorities are instantly alerted with the footage and information they need.
- Continuous Learning: Our models improve over time, learning from past incidents and adapting to new environments.
Our solution operates on a SaaS (Software as a Service) model, with the flexibility to scale across different customer types:
- Basic Subscription: Real-time monitoring, gender classification, and alerts.
- Premium Subscription: Advanced analytics, detailed incident reporting, and hotspot prediction features for long-term planning.
We prioritize data privacy and security. Our system is compliant with regulations like GDPR and uses end-to-end encryption for all data streams, ensuring that sensitive information is protected at all times.
- Proactive Prevention: Unlike manual monitoring or apps that depend on user input, our system works in the background, 24/7, to detect and alert potential threats before they escalate.
- Cost-Effective: Integrates with existing infrastructure, minimizing the need for additional hardware or costly upgrades.
- Scalable & Adaptable: From cities to small campuses, our solution grows with your needs.
- Social Good: Empower communities to feel safer and foster a proactive approach to public safety.
We welcome contributions to make SafeAura even better! Whether you're a developer, researcher, or just passionate about women’s safety, there’s a role for you.
- Fork the repository
- Make your changes
- Submit a pull request
Let’s work together to make public spaces safer for everyone!
In the next 5 years, we envision SafeAura as a key player in public safety solutions worldwide. Our goal is to expand this technology to other areas of safety and security, from detecting suspicious activity in public transport to ensuring the safety of children in schools.
Want to try out SafeAura? Follow these simple steps to get started:
- Clone this repository:
https://github.com/arunimasharma33/Women-Safety.git
- Install dependencies:
pip install -r requirements.txt
- Run the application:
python app.py