AlphaRescue 🚨

"First to know, First to act!"

An AI-powered emergency dispatch system designed to rapidly respond to distress calls by intelligently coordinating with emergency authorities.

🏆 Winner: Fetch AI Best Use of Fetch AI - UC Berkeley AI Hackathon 2025

🌟 Overview

AlphaRescue revolutionizes emergency response by combining cutting-edge AI technologies with autonomous agent networks to create a faster, more intelligent dispatch system. Our platform processes emergency calls in real-time, automatically assesses situations, and coordinates with the appropriate emergency services.

✨ Key Features

• 🎙️ Voice-based AI Assistant: Powered by VAPI for natural emergency call handling
• 📝 Real-time Call Transcription: Automatic summarization using Gemini AI
• 🤖 Autonomous Agent Network: Intelligent situation assessment and resource allocation
• 🏥 Smart Facility Selection: Geolocation-based hospital and emergency service matching
• 📊 Real-time Dashboard: Live incident monitoring and tracking
• 🚑 Intelligent Ambulance Dispatch: Automated selection of appropriate ambulance types

🛠️ Technologies Used

Frontend

• React.js with TypeScript
• Tailwind CSS for styling
• Mapbox GL for mapping
• Lucide React for icons

Backend

• Node.js with Express
• Python for AI agents
• Fetch.ai uAgents for autonomous agents
• Supabase for database and real-time features

AI & ML

• Gemini AI for transcription and summarization
• Groq LLM for fast inference
• OpenAI for additional AI capabilities

Infrastructure

• Vercel for deployment
• VAPI for voice integration

🚀 Getting Started

Prerequisites

• Node.js (v16 or higher)
• Python 3.8+
• Supabase account
• API keys for Gemini, Groq, and VAPI

Installation

1. Clone the repository

   git clone https://github.com/yourusername/Alpha-Rescue.git
   cd Alpha-Rescue

2. Setup Frontend Dashboard

   cd Dashboard/dashboard-frontend
   npm install
   npm start

3. Setup Backend Dashboard

   cd Dashboard/dashboard-backend
   npm install
   npm start

4. Setup Python Agents

   cd fetch-agent-fire-responder
   pip install -r requirements.txt
   python Orchestrator.py

Environment Variables

Create .env files in the respective directories with:

# Supabase
SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key

# AI Services
GEMINI_API_KEY=your_gemini_key
GROQ_API_KEY=your_groq_key
OPENAI_API_KEY=your_openai_key

# VAPI
VAPI_API_KEY=your_vapi_key

# Mapbox
MAPBOX_ACCESS_TOKEN=your_mapbox_token

📁 Project Structure

Alpha-Rescue/
├── Dashboard/
│   ├── dashboard-frontend/     # React frontend application
│   │   ├── src/
│   │   │   ├── components/     # React components
│   │   │   └── types.ts        # TypeScript definitions
│   │   └── package.json
│   └── dashboard-backend/      # Express.js backend
│       ├── server.js           # Main server file
│       └── package.json
└── fetch-agent-fire-responder/ # Python agents
    ├── Orchestrator.py         # Main orchestrator agent
    ├── paramedic/              # Paramedic agents
    │   ├── ambulance_agent.py  # Ambulance dispatch logic
    │   └── groq_classifier.py  # AI classification
    ├── hospital_agent.py       # Hospital matching agent
    ├── firestation_lookup_agent.py # Fire station agent
    ├── police_integration.py   # Police coordination
    └── requirements.txt        # Python dependencies

🎯 How It Works

1. Emergency Call Received: VAPI processes incoming voice calls
2. Real-time Transcription: Gemini AI transcribes and summarizes the call
3. Agent Network Activation: Fetch.ai agents assess the situation
4. Resource Allocation: System identifies optimal emergency services
5. Dispatch Coordination: Automated coordination with hospitals, fire stations, or police
6. Real-time Monitoring: Dashboard provides live updates on incident status

🏆 Achievements

• UC Berkeley AI Hackathon 2025 Winner: Fetch AI Best Use of Fetch AI
• Successfully demonstrated end-to-end emergency response automation
• Integrated multiple AI technologies into a cohesive system
• Built scalable microservice architecture

🚧 Challenges Overcome

• Multi-agent Communication: Synchronized communication between distributed agents
• Agent Registration Management: Efficient handling of agent lifecycle
• Spam Call Detection: AI-powered filtering of non-emergency calls
• LLM Edge Cases: Robust handling of AI classification uncertainties

🔮 What's Next

• Trust & Reputation Layer: Add reliability scoring for emergency services
• Multi-modal Support: Voice, text, and image-based emergency reporting
• Extended Coverage: Support for fire department and police emergencies
• Mobile-first Frontend: Dedicated mobile application
• Custom Model Training: Train internal models with incident data
• Real-world Deployment: Partner with emergency services for pilot programs

📄 License

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

🤝 Contributing

We welcome contributions! Please feel free to submit a Pull Request.

📞 Contact

For questions or support, please reach out to the team through our GitHub repository.

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AlphaRescue - Transforming emergency response through AI innovation. 🚑✨