Inspiration
During medical emergencies, every minute can make a difference, especially during the critical Golden Hour. Ambulances often face delays because of heavy traffic, congested junctions, and limited communication between ambulance drivers and traffic authorities.
Although emergency ambulance services provide transportation, they do not always ensure that the route is cleared before the ambulance arrives. This inspired us to develop the Ambulance Alert System for Traffic Clearance, focusing on better coordination between ambulances and traffic authorities.
What it does
The Ambulance Alert System uses GPS-based real-time tracking to monitor an ambulance during an emergency.
The system identifies the ambulance's route, detects important junctions and traffic-prone areas, and generates early alerts for nearby traffic police or control points.
These alerts allow traffic authorities to prepare in advance, manage traffic, and clear the road before the ambulance reaches the junction. The system continuously monitors the ambulance and can update route information and alerts if the route changes or unexpected traffic conditions occur.
Our main goal is to reduce unnecessary ambulance travel delays and improve the chances of reaching the hospital within the Golden Hour.
How we built it
We designed the system using a client-server architecture.
- Frontend: HTML, CSS, JavaScript
- Map Visualization: Leaflet.js
- Backend: Python
- Database: MySQL
- Location Tracking: GPS
GPS data from the ambulance is processed by the Python backend. The system determines the route and identifies important junctions along the path.
MySQL stores ambulance location records, route and junction information, alert logs, and timestamps. The web dashboard allows traffic authorities to monitor ambulance movement and receive alerts.
The overall workflow is:
Emergency Call → Ambulance Dispatch → GPS Tracking → Route & Junction Identification → Early Alert → Traffic Clearance → Continuous Monitoring → Hospital
Challenges we ran into
One of our major challenges was designing a system that could coordinate real-time ambulance tracking with traffic alerts.
We also had to consider how to identify important junctions along the ambulance route and send alerts early enough for traffic authorities to respond.
Another challenge is the dependency on GPS accuracy and stable internet connectivity. In real-world environments such as tunnels or areas with weak network coverage, location updates and alerts may be affected.
We also identified that successful traffic clearance depends on the timely response and coordination of traffic authorities.
Accomplishments that we're proud of
We are proud of developing a complete concept and prototype architecture that connects ambulance tracking, route identification, early traffic alerts, and traffic coordination into one system.
Our simulated experiments showed a reduction in estimated ambulance travel time from 25–30 minutes to 15–18 minutes, while junction delays decreased from 8–10 minutes to 2–3 minutes.
We are also proud that our approach focuses on proactive traffic clearance, where authorities receive information before the ambulance reaches a junction rather than reacting after it arrives.
What we learned
Through this project, we learned how real-time GPS tracking, route analysis, web technologies, databases, and automated alerts can work together to address an emergency-response problem.
We also learned about designing communication between multiple components, including the ambulance, emergency coordination center, traffic authorities, and data management system.
Most importantly, we learned that building a real-world emergency system requires considering practical limitations such as GPS accuracy, network availability, traffic infrastructure, and human coordination.
What's next for Ambulance Alert System For Traffic Clearance
Our next step is to move beyond the simulated environment and work toward real-world testing.
We plan to explore AI/ML-based traffic prediction to identify congestion more accurately and recommend efficient routes. We also want to explore integration with automatic traffic-light control so that signals can prioritize approaching ambulances.
Future development could include a dedicated mobile application for traffic authorities and emergency workers, integration with the 108 ambulance network, and IoT/V2I communication for direct interaction between ambulances and traffic infrastructure.
We also aim to improve GPS accuracy, network reliability, security, and scalability before large-scale real-world deployment.
Log in or sign up for Devpost to join the conversation.