RTACC is an advanced AI-powered crisis detection and emergency response system that leverages NVIDIA GPU acceleration to monitor multiple data streams in real-time and predict emergency situations before they escalate.

RTACC analyzes weather conditions, traffic patterns, social media sentiment, and news reports using machine learning to:

• 🔍 Detect emerging crises 30+ minutes before escalation
• 📊 Predict crisis evolution with confidence scoring
• 🚀 Recommend optimal resource deployment for emergency response
• 🌍 Monitor any global location with dynamic map visualization

┌─────────────────┐    ┌────────────────────┐    ┌─────────────────┐
│   Data Sources  │───▶│  CUDA Processor    │───▶│   Dashboard     │
├─────────────────┤    ├────────────────────┤    ├─────────────────┤
│ • Weather APIs  │    │ • PyTorch NNs      │    │ • Streamlit UI  │
│ • Traffic Data  │    │ • Scikit-learn     │    │ • Plotly Maps   │
│ • Reddit API    │    │ • GPU Acceleration │    │ • Real-time     │
│ • News Feeds    │    │ • Anomaly Detection│    │ • Multi-location│
└─────────────────┘    └────────────────────┘    └─────────────────┘

• 🔥 NVIDIA CUDA: PyTorch neural networks running on GPU
• ⚡ Tensor Operations: Real-time multi-source data fusion
• 🧠 GPU Memory: Optimized for continuous data processing
• 📊 Mixed Precision: Faster inference with maintained accuracy

• Python 3.8+
• NVIDIA GPU with CUDA support (recommended)
• 8GB+ RAM (16GB+ recommended)
• Internet connection for API access

Project Maintainer: Nodshley Marcelin

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