Research Article

, 12 Dec 2025 | 10.6234610.62346/ijcn_q4_v13_no4_25_08
Year : 2025 | Volume: 13 | Issue: 4 | Pages : 1-4

Breath-Based Alcohol Detection in Smart Helmets: A Microcontroller-Driven Safety Solution

Dr. R. Samson Daniel 1 *, Jayasri c, Boomidevi S
  • 1Anna University Chennai, Associate Professor, Department of ECE, K. Ramakrishnan college of engineering, Tamilnadu, IN
Drink and drive detection is of interest because it may prevent accidents that are primarily caused by excessive alcohol consumption. There is currently a lot of research being done to develop detection techniques for alcohol limits that cause unconsciousness and impair human ability to walk, work, and comprehend. Utilizing the importance of electronics and automotive parts, components, and concepts is the main way that the research is accomplished. There are many different types of devices, such as various MQ series sensors and devices that read facial expressions. Among these, the MQ-3 Sensor, which measures the amount of alcohol in people, has demonstrated promise in the field of electronics. This article outlines a system and apparatus known as an alcohol sensor device that measures a person's alcohol intake. This device measures the concentration of alcohol, and if it exceeds a certain threshold, the car's ignition mechanism is stopped, meaning it won't start. We can prevent accidents caused by drinking and driving by using the aforementioned device. As everyone knows, driving while intoxicated is extremely risky. People won't be able to control their behavior and will react slowly. When operating a vehicle while intoxicated, drivers are unable to handle emergency situations. According to a 2008 World Health Organization study, drunk driving is a contributing factor in between 50% and 60% of traffic accidents. The primary cause of the deadly car accident has been identified as drunk driving.

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Keywords: Alcohol Sensor, Alcohol Detector; LCD: MQ3

Citation: Dr. R. Samson Daniel*, Dr. R. Samson Daniel ( 2025), Breath-Based Alcohol Detection in Smart Helmets: A Microcontroller-Driven Safety Solution. , 13(4): 1-4

Received: 30/11/2025; Accepted: 12/12/2025;
Published: 12/12/2025

Edited by:

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*Correspondence: Dr. R. Samson Daniel , samson.rapheal@gmail.com


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