Real-Time Emergency Response Optimization with AI Triage

Overview

This project was developed for a hackathon and aims to optimize emergency response using AI triage. The project includes a mobile app, backend server, and a custom-trained spaCy model for Named Entity Recognition (NER). The app allows users to call for help, extract key details from their voice calls using speech-to-text models, and provide certified first aid tips based on the extracted information. Additionally, users can book ambulances through the app's map interface.

Tech Stack

• Mobile App: Flutter
• Backend: Django
• Database: MySQL
• Design: Figma File

Features

• Real-time emergency response optimization
• Speech-to-text for call transcription
• Custom-trained spaCy model for NER
• Extraction of symptoms and conditions from voice transcripts
• Certified first aid tips based on extracted information
• Ambulance booking via map interface

Setup

To set up the project, follow these steps:

1. Clone the repository.
2. Set up the backend server using Django and MySQL.
3. Install dependencies for the mobile app using Flutter.
4. Run the predictor service on any linux based PC (It is a flask server)
5. Run the app on a compatible device or emulator.

Usage

• Use the app to call for help in emergency situations.
• Speak clearly to allow the app to transcribe your voice call.
• Follow the app's instructions for first aid tips and ambulance booking.

Team Members

• Aarchi
• Dhruv
• Pranav
• Utsah

Made with ❤️ by Team BKL (Bahut Kaam ke Log)