Kwik is an AI-powered emergency dispatch system designed to optimise India's 112 emergency response system. It addresses critical challenges within the 112 Emergency Response Support System (ERSS), aiming to improve public safety and well-being for the citizens of India.

Kwik is developed for a dual target audience: direct operational users (emergency dispatchers and operators) and ultimate beneficiaries (the Indian people/citizens).

• Overwhelming Call Volume: Dispatchers are inundated with a massive influx of non-emergency, prank, and blank calls. For instance, in Delhi, approximately 10,000 out of 15,672 daily calls are blank, leading to dispatcher stress, cognitive overload, potential errors, and dangerous delays in responding to real emergencies.
• Repetitive Workflows and Manual Coordination: Operators often struggle with repeated low-priority calls and slow manual coordination, which can lead to burnout.
• Language Barriers: India's significant linguistic diversity poses a challenge for human operators to communicate effectively with all callers, with regional language coverage varying.
• Difficulty in Information Extraction and Decision Making: Manually assessing call severity, urgency, and resource needs is slow and prone to error.
• Lack of Empathy and Emotional Support Tools: Distressed callers in traumatic situations may not consistently receive empathetic emotional support.
• Need for Real-Time Oversight: Dispatchers require real-time oversight of resources to efficiently dispatch services.

• Long Wait Times and Slow Response: The current 112 system in India faces challenges with average response times ranging from 12 to 24 minutes, with reports of delays and public dissatisfaction. An ambulance was reported to be stuck for five hours in Nainital due to traffic congestion.
• Lack of Accessibility due to Language Barriers: India's vast linguistic diversity, with over 22 scheduled languages and numerous dialects, can hinder effective communication.
• Inconsistent Emotional Support During Emergencies: Callers experiencing traumatic events may not receive empathetic handling consistently.
• Delays due to Traffic and Poor Infrastructure: Traffic congestion and poor infrastructure cause significant delays for emergency vehicles.
• Risk of Missed or Delayed Critical Responses: With a high volume of non-emergency and blank calls, genuine emergencies may be delayed or missed, impacting positive outcomes for citizens in distress.
• Fragmented System: Despite the 112 initiative, the emergency response system remains fragmented, with varying protocols and contact numbers leading to inefficiencies and confusion.
• Gaps in Pre-hospital Emergency Services: This includes insufficient ambulance availability, shortages of well-trained Emergency Medical Technicians (EMTs), and underdeveloped technology integration.

Kwik proposes an AI-driven solution to address these problems, leveraging advanced technologies to enhance efficiency and empathy in emergency call handling.

• Real-Time Emergency Filtering: The AI automatically filters out blank and non-emergency calls, allowing dispatchers to focus on genuine emergencies. Kwik targets 97–99% accuracy in detecting such calls, optimised for Indian dialects and languages.
• AI-Powered Triage: Evaluates call severity, urgency, and resource needs, providing action recommendations (e.g., dispatch police, ambulance, fire). It aims for a triage latency of under 2 seconds.
• Language Translation & Multilingual Support: Offers features like Hindi ↔ Tamil ↔ Telugu ↔ English ↔ Bengali translation, enhancing accessibility for callers from diverse linguistic backgrounds.
• Emotion Detection & Empathetic AI Responses: Utilises Sentiment AI (e.g., Hume EVI, NVIDIA Riva) to analyse caller tone, allowing the AI to provide empathetic responses, calm callers, and maintain clear communication.
• Auto-Documentation: Converts audio into call logs and incident reports, freeing up dispatchers' time.

• Smart Routing Dashboard & Real-Time Incident Dashboard: Displays live emergencies and unit statuses, supporting faster and more informed dispatching decisions and enhancing dispatch efficiency.
• GPS Tracking & Automated Emergency Corridors: Incorporates GPS tracking for emergency vehicles and integrates AI with traffic systems to clear routes, ensuring faster arrival of first responders.
• Integration with ERSS Systems: Designed to integrate with 112 India backend APIs, GPS services, and radio communication channels.

• Kwik operates on a human-in-the-loop principle, meaning the AI supports and assists human dispatchers with information and recommendations, but it never replaces their final decisions, ensuring human control and accountability in critical emergency situations.

By implementing Kwik, the project aims to significantly enhance India's emergency response capabilities. This includes:

• Reducing dispatcher workload and fatigue.
• Speeding up critical response dispatch and improving overall response times. Kwik aims for dispatch within 15 minutes in urban areas and 30 minutes in rural areas.
• Improving caller experience with empathy and trust.
• Critically, saving thousands of lives annually, with the economic value of lives saved potentially reaching Rs 5,000 crore yearly.
• It also has the potential to save up to Rs 96 crore annually in operational costs by reducing the need for human operators.

To run the Kwik dashboard locally, you need to start three separate servers in three different terminal windows.

• Node.js
• A separate clone of the hume repository (from https://github.com/areycruzer/hume) in the same parent directory as the kwik project.
• You must have a .env.local file in the hume project directory with the necessary Hume AI API keys.

This server handles the database connection and the main API.

# In PowerShell, navigate to the project directory
cd "C:\Users\swyam\Desktop\New folder (4)\kwik"
node server/index.js

This will start the backend on http://localhost:3001.

This server runs the voice call interface that is embedded in the dashboard.

# Navigate to the hume directory (should be in the same parent directory)
cd "..\hume"
npm run dev -- -p 3003

This will start the Hume EVI server on http://localhost:3003.

This server runs the main dashboard user interface.

# Navigate back to the kwik directory
cd "..\kwik"
npm run dev

This will start the frontend on http://localhost:5173 (or the next available port). You can then access the dashboard at this URL.

• Frontend: React with TypeScript, Vite, Tailwind CSS, shadcn/ui
• Backend: Node.js with Express
• AI Integration: Hume AI for emotion detection and voice processing
• Real-time Communication: WebSocket integration
• Styling: Tailwind CSS with custom components

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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

For questions or support, please contact the development team.