AI Based Emergency Assist System for Ambulance

India is one of the most popular countries in the world and provides significant health care support to people. Managing the emergency vehicles with lifesaving benefits are highly demanded. During uncertain situations, the need for life saving support. The proposed approach incorporates a microcontroller-enabled smart system capable of detecting a patient's critical condition using a heartbeat sensor, a respiratory sensor, and an AI-driven voice assistant. This system facilitates automated control and immediate activation of necessary life-saving measures. Real-time patient data is continuously monitored and uploaded to an Internet of Things (IoT)-enabled cloud platform, ensuring secure access through fingerprint authentication. In emergency scenarios, the system grants authorized access to provide timely medical intervention to the patient. Additionally, the AI-driven voice assistant sends alerts about accidents, including the patient's authorized demographic details, to relevant authorities such as the police and the nearest hospital. This ensures that the Intensive Care Unit (ICU) is preemptively notified and prepared for the patient's arrival. The automated framework is designed to eliminate delays associated with manual processing, enabling swift and efficient responses during emergencies. By streamlining communication and providing immediate support, the system significantly enhances the likelihood of saving lives in critical situations.

Authors

Institutions

Publication Details

Published
2025-02-05
DOI
https://doi.org/10.1109/idciot64235.2025.10914913
Citations
2
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
1.43
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI Based Emergency Assist System for Ambulance

Anoop Dev Anoop Dev, M. Angelin Ponrani, S Dhammodharan
2 citations
IoT and GPS-based Vehicle Safety Systems
1.43
article

AI Based Emergency Assist System for Ambulance

Anoop Dev Anoop Dev, M. Angelin Ponrani, S Dhammodharan
article en
2 citations

Abstract

India is one of the most popular countries in the world and provides significant health care support to people. Managing the emergency vehicles with lifesaving benefits are highly demanded. During uncertain situations, the need for life saving support. The proposed approach incorporates a microcontroller-enabled smart system capable of detecting a patient's critical condition using a heartbeat sensor, a respiratory sensor, and an AI-driven voice assistant. This system facilitates automated control and immediate activation of necessary life-saving measures. Real-time patient data is continuously monitored and uploaded to an Internet of Things (IoT)-enabled cloud platform, ensuring secure access through fingerprint authentication. In emergency scenarios, the system grants authorized access to provide timely medical intervention to the patient. Additionally, the AI-driven voice assistant sends alerts about accidents, including the patient's authorized demographic details, to relevant authorities such as the police and the nearest hospital. This ensures that the Intensive Care Unit (ICU) is preemptively notified and prepared for the patient's arrival. The automated framework is designed to eliminate delays associated with manual processing, enabling swift and efficient responses during emergencies. By streamlining communication and providing immediate support, the system significantly enhances the likelihood of saving lives in critical situations.

St. Joseph's Institute of Technology (IN)
Affordable and clean energy
Openalex Percentile: Top 22%
IoT and GPS-based Vehicle Safety Systems
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.