An Intelligent In-Cabin Health Monitoring and Automated Emergency Response System Using Real-Time Data Analysis

Abstract

Road accidents caused by sudden health issues of drivers are a major concern in the world. Situations such as heart attack, abnormal body temperature, or low oxygen levels can cause loss of vehicle control. To solve this issue, this paper presents an in-cabin health monitoring and emergency response system using ESP32. The proposed system continuously monitors vital parameters of the driver, including heart rate, body temperature, and oxygen saturation (SpO?). These parameters are measured and transmitted to an IoT platform-Blynk Iot for real-time observation. If any abnormal or emergency condition is detected, the system activates an emergency protocol that includes alert generation using a buzzer, activation of hazard lights through a relay module, and reduction of vehicle speed using a motor driver. Additionally, GPS and GSM modules are integrated to provide location tracking and alert communication. The system focuses on ensuring that the vehicle safely slows down and parks at the roadside, minimizing accident risk. Our proposed system is cost-effective and suitable for real-time applications in modern vehicles.

Introduction

Road accidents caused by sudden driver health emergencies, such as cardiac arrest, abnormal body temperature, or low oxygen levels, have become a major safety concern. Existing vehicle safety systems primarily focus on external threats like collisions and obstacle detection, while giving little attention to the driver's health condition. Although some IoT-based monitoring systems can track vital signs and generate alerts, most lack automated emergency response mechanisms.

To address this gap, the proposed system introduces a real-time in-cabin driver health monitoring and emergency response system based on the ESP32 microcontroller. The system continuously monitors vital health parameters, including heart rate, body temperature, and blood oxygen (SpO?) levels, using integrated sensors. Data is processed by the ESP32 and transmitted to the Blynk IoT platform for real-time monitoring through a mobile application.

The system follows a structured workflow consisting of data acquisition, processing, IoT monitoring, emergency detection, and emergency response. Sensor readings are continuously compared with predefined threshold values. If an abnormal condition is detected, the system automatically triggers multiple safety actions. These include activating a buzzer, turning on vehicle hazard lights, gradually reducing vehicle speed, safely stopping the vehicle at the roadside, and sending emergency alerts with the vehicle’s location through GPS and GSM modules.

The architecture is divided into four layers: sensing, processing, communication, and response. The sensing layer collects physiological data, the ESP32 processing layer analyzes the data, the communication layer handles IoT monitoring and emergency notifications, and the response layer executes vehicle safety measures.

The proposed system offers several advantages, including real-time health monitoring, fast emergency detection, reliable communication, automated vehicle control, and improved road safety. It is designed as a cost-effective solution suitable for both private and commercial vehicles without requiring major vehicle modifications.

Potential applications include personal vehicles, public transportation, fleet management systems, emergency services, smart vehicles, and future autonomous or semi-autonomous vehicles. Overall, the system provides an integrated approach that combines health monitoring, IoT communication, and automatic vehicle control to reduce accident risks and enhance driver safety.

Conclusion

The proposed ESP32-based in-cabin health monitoring system provides continuous real-time monitoring of driver vital signs, including heart rate, body temperature, and SpO?. In case of abnormal conditions, it automatically triggers emergency responses such as reducing vehicle speed, activating hazard lights, sounding an alert buzzer, and sending location-based notifications via GPS and GSM. By combining IoT-based remote monitoring with automated vehicle control, the system significantly enhances driver safety, reduces the risk of accidents caused by sudden health issues, and demonstrates a cost-effective solution suitable for modern smart vehicles. Overall, this project showcases an integrated approach to proactive road safety and emergency management.

References

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Copyright

Copyright © 2026 Sainath Borule, Prathamesh Borse, Vivek Godbole, Gaurav Lokhande, Kuldeep Waje, Prof. Nilesh Kuchekar. 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.