Design and Implementation of Smart-Alert System with Engine Immobilization

Abstract

This study introduces a practical, tech-driven approach to tackling road accidents caused bydrunk driving—a persistent issue even after speed limits and other preventive measures. While reckless driving, speeding,andalcoholimpairmentremain leadingcauses ofcrashes,ourteamhasdesignedaninnovativeIoT- based in-vehicle system using an ESP32 microcontroller. ThesetupintegratesanMQ3alcoholdetectionsensor, DC motor and a L298 dual H-bridge motor driver to control vehicle movementAt its core, the Alcohol detection sensor continuously tracks the driver’s breath for alcohol levels, cleverly embeddedintothesteeringwheelforseamlessoperation. If the alcohol concentration exceeds the legal thresholdof 0.5 mg/mL, the system doesn’t just sound an alarm— it automatically alerts designated contacts or authorities via SMS. It also monitors speeding, adding an extralayer of safety.During testing, the alcohol sensor proved both fast and reliable, reacting instantly to alcohol detection and maintaining consistent performance over time. By merging real-time alerts with cloud connectivity, this system offers a user-friendly, proactive solution to curb impaired driving and save lives.

Introduction

Background & Problem Statement

Road safety is a major public concern globally. Drunk driving and speeding are two leading causes of road accidents, injuries, and fatalities. Despite laws and awareness campaigns, alcohol-related traffic incidents remain high, especially in countries like India where underreporting and weak enforcement skew official data. In 2022, over 461,000 road accidents were recorded in India, with a significant portion related to reckless or impaired driving.

Objective of the Research

This project aims to prevent drunk driving and overspeeding by implementing an IoT-enabled system that:

• Detects alcohol on the driver’s breath

• Monitors vehicle speed

• Sends real-time alerts via SMS

• Can disable the vehicle engine when necessary

System Overview

The solution involves a dual-microcontroller architecture using ESP32 boards. It integrates sensors, wireless communication modules, and a vehicle control system to detect unsafe driving behavior and respond autonomously.

Key Components:

• MQ-3 Alcohol Sensor: Detects alcohol vapors

• Optical Speed Sensor: Monitors speed in real time

• ESP32 Microcontrollers: Central processing units with Wi-Fi/Bluetooth capability

• A9G GSM/GPS Module: Sends SMS alerts and tracks location

• L298N Motor Driver & Servo Motors: Controls vehicle movement and steering

• Relay Module: Cuts off ignition or halts the vehicle

• GUI Interface: Allows users to configure speed limits and receive alerts

Functionality

• If alcohol is detected above a threshold, the system:

  • Blocks vehicle ignition

  • Sends an SMS alert with GPS location

  • Flashes warning LEDs

• If the speed limit is exceeded:

  • The system intervenes by gradually stopping the vehicle

  • Sends real-time alerts to family members or authorities

• In emergencies, the driver can override the lock, but authorities are still alerted to ensure safety

Results

• The system successfully detected alcohol using breath samples and prevented vehicle ignition when above threshold (set at 3500 analog value).

• SMS alerts with Google Maps links were reliably sent within seconds of violation detection.

• The vehicle performed smooth and controlled stops in unsafe conditions.

• Speed thresholds were tested (normal: 100–120 km/h; excessive: >120 km/h), triggering alerts accordingly.

• Dual-core ESP32 performance remained stable throughout testing.

Advantages

• Prevents accidents caused by drunk or reckless driving

• Real-time data transmission enhances accountability and response

• Provides remote monitoring for authorities and family members

• Emergency override ensures flexibility in critical situations

• Promotes behavioral change among drivers, especially in the commercial transport sector

Limitations

• Environmental and behavioral factors can affect sensor performance (e.g., if a driver wears a mask or obstructs the sensor).

• Maintenance and user awareness are necessary to ensure long-term reliability.

Conclusion

This project successfully implements a real-time,autonomous vehicle safety system capable of detecting alcohol intoxication and responding appropriately by halting the vehicle and alerting authorities or family with precise GPS-based SMS alerts. Built entirely on ESP32 and A9G modules, the design offers improved processing, dual-core parallelism, and complete automation, including simulated hardware activation.Compared to traditional microcontroller systems, thisdesign standsoutintermsofmultitasking,communicationcapability,and reducedmanual effort.Futureenhancements mayincludeintegrationwithvoice-activatedinterfaces, temperature/humiditycompensationinsensorreadings,and black-box style trip logging. The proposed solution is highly suitable forpractical deploymentin regions where impaired driving is a significant threat. Toimprovefutureiterations,wesuggest:-. 1) Integratevoicerecognitiontorestrictbreathteststo authorized users (e.g., the car owner). 2) Includehumidity/temperaturesensorstoadjustreadings for environmental factors.

Copyright

Copyright © 2025 Neha ., Ayush K Santhosh, Tushar Prajapati, Rakesh Kumar Yadav. 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.