Iot Based Health and Alcohol Monitoring and Safety Control System
Authors
Sadhu Prasanth
Assistant professor, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India. (IN)
G. Murali krishna
UG students, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India (IN)
M. Kishore
UG students, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India DOI: https://doi.org/10.51583/IJLTEMAS.2026.150300029 (IN)
K. Jagannadham
UG students, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India (IN)
B. Bhaskararao
UG students, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India (IN)
P. Sravan kumar
UG students, Department of Mechanical Engineering, Satya Institute of Technology and Management Vizianagaram Andhra Pradesh, India (IN)
Article Information
DOI: 10.51583/IJLTEMAS.2026.150300029
Subject Category: Mechanical Engineering
Volume/Issue: 15/3 | Page No: 357-362
Publication Timeline
Submitted: 2026-04-06
Published: 2026-04-04
Abstract
This paper presents the design and implementation of an Internet of Things (IoT)-based Health and Alcohol Monitoring and Safety Control System aimed at enhancing safety in industrial, transportation, and other safety-critical environments. Accidents caused by alcohol consumption and abnormal health conditions pose significant risks, while traditional monitoring methods are often manual, inefficient, and lack real-time capabilities.
The proposed system integrates multiple sensors, including an MQ-3 alcohol sensor, heart rate sensor, blood pressure sensor, and DS18B20 temperature sensor, to continuously monitor physiological parameters of individuals. The collected data is processed using an ESP32 microcontroller, which analyzes sensor values and compares them with predefined safety thresholds to determine the user’s fitness for operation.
When abnormal conditions are detected, the system activates alert mechanisms such as a buzzer and LCD display notifications, and can restrict access to machinery or workplace environments. Furthermore, the system utilizes Wi-Fi connectivity to transmit real-time data to an IoT cloud platform, enabling remote monitoring, data logging, and safety analysis through web or mobile interfaces.
Experimental results demonstrate that the system accurately detects unsafe conditions and responds in real time, thereby reducing human error and improving overall safety. The proposed solution offers a reliable, scalable, and cost-effective approach for preventing accidents and enhancing safety monitoring in modern industrial applications.
Keywords
Alcohol sensor, Heart rate sensor, Blood pressure sensor, DS18B20 temperature sensor, ESP32 microcontroller
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References
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