Ambugency: Emergency Ambulance Booking Service

Abstract

The current research paper includes the comprehensive and original study of Ambugency, the next-generation web platform, which provides real-time ambulance bookings, better patient-to-hospital coordination, reduced response and dispatch delays, and provided faster and efficient delivery of emergency care. One of the foundations of healthcare systems all over the world is emergency medical transportation, but current models are typically flawed due to slow dispatch, absence of real-time tracking, and poor integration with hospitals. The paper reflects on the findings of over ten recent studies, industry white papers, and real-life ambulance network implementations between 2015 and 2025 to develop a backbone to a sophisticated ambulance booking ecosystem. The paper highlights four main pillars which include GPS-based live tracking, route optimization using AI and hospital coordination. The paper suggests a strong architecture in addition to pinpointing gaps in the existing solutions which are critical. The goal is to create a platform that is scalable and inclusive and can work in both urban and rural areas with limited bandwidth. The results indicate that thousands of lives can be saved each year with the help of Ambugency that reduces response time, improves transparency, and prepares emergency departments.

Introduction

The paper proposes Ambugency, an AI-powered emergency ambulance booking and coordination system designed to reduce delays in critical medical situations such as heart attacks, strokes, and accidents, where response time is vital for survival.

Currently, ambulance services rely heavily on manual phone-based booking, which causes delays due to poor location communication, human errors, and slow dispatch coordination. Ambugency aims to solve these issues using GPS, AI/ML, and real-time communication technologies to automate ambulance allocation, optimize routes, and improve hospital coordination.

The system is built using a microservices architecture and includes key modules such as a Progressive Web App (PWA) for users, an AI-driven dispatch engine, real-time GPS tracking with traffic-aware routing, and hospital integration for early preparation before patient arrival. It also ensures scalability, fast response times, and reliability across urban and rural areas.

Security is addressed through encryption, role-based access control (RBAC), and compliance with data protection standards. The system is designed to be scalable using cloud infrastructure and capable of handling high emergency loads.

The methodology involves literature review, system design, implementation, and simulation-based testing using KPIs like response time and dispatch accuracy. Challenges such as inaccurate location detection, traffic unpredictability, hospital coordination gaps, and data privacy risks are addressed through hybrid GPS methods, smart routing, secure APIs, and encryption.

Conclusion

Overall, Ambugency provides a unified, intelligent emergency response platform that improves ambulance dispatch speed, coordination, transparency, and patient survival outcomes.

References

[1] R. Kumar and S. Patel, “Real-Time GPS Tracking in Emergency Medical Services,” ResearchGate, 2023. [2] A. Singh and M. Verma, “Web and Mobile-Based Ambulance Booking Applications: A Hybrid Approach,” Nature Scientific Reports, 2024. [3] L. Sharma, P. Rao, and N. Kaur, “Recent Advances in Web-Based Emergency Healthcare Systems,” MDPI Healthcare Informatics, 2023 . [4] T. Gupta and D. Mehta, “An Effective IoT-Based Framework for Smart Ambulance Services,” ScienceDirect – Expert Systems with Applications, 2025. [5] S. Das and A. Chakraborty, “AI-Driven Ambulance Dispatch and Route Optimization,” ResearchGate, 2025. [6] V. Nair, R. Bose, and K. Menon, “A Nationwide Emergency Ambulance Network Using Cloud and Machine Learning,” IEEE Xplore, 2024. [7] M. Joshi and H. Deshmukh, “Enhancing Ambulance Response Times through GPS and Cloud Integration,” arXiv, 2024. [8] P. Thakur and R. Sinha, “Real-Time Ambulance Booking Systems: Opportunities and Challenges,” IRJET, 2023. [9] D. Khan and F. Ali, “Web-Based Emergency Response Platforms: A Comparative Study,” TechRxiv, 2023. [10] S. Iyer, A. Bhat, and R. Pillai, “A High-Accuracy Real-Time Ambulance Allocation System Using Cloud and AI,” ScienceDirect – Smart Healthcare Systems, 2025.

Copyright

Copyright © 2026 Harsh Pal, Suryam Pandey, Tritam Panja, Apeksha Waghmare. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.