IoT-enabled Drowsiness Driver Safety Alert System with Real-Time Monitoring Using Integrated Sensors Technology

2025-02-01

AI Summary

To address traffic accident risks caused by drunk and drowsy driving, this study proposes and implements an IoT-based real-time dual-mode warning system. The system integrates an MQ-3 alcohol sensor and an infrared reflective eye-movement sensor to establish a novel synergistic detection mechanism for concurrent identification of drunk and fatigued driving states. It enables millisecond-level sensing and progressive vehicle intervention—including audible/visual alerts, active speed reduction, and emergency braking—executed via an ARM microcontroller running embedded real-time algorithms and transmitting data to mobile devices over Bluetooth. Experimental validation demonstrates a drunk-driving response latency of ≤15 seconds, 98.2% accuracy in fatigue detection for eye-closure durations ≥1.5 s, and reliable activation of multi-level braking protocols. By overcoming the limitations of single-factor monitoring, the system significantly enhances the closed-loop capability of proactive driving safety.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Activity and Plan Recognition
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

Significant losses in terms of life and property occur from road traffic accidents, which are often caused by drunk and drowsy drivers. Reducing accidents requires effective detection of alcohol impairment and drowsiness as well as real-time driver monitoring. This paper aims to create an Internet of Things (IoT)--enabled Drowsiness Driver Safety Alert System with Real-Time Monitoring Using Integrated Sensors Technology. The system features an alcohol sensor and an IR sensor for detecting alcohol presence and monitoring driver eye movements, respectively. Upon detecting alcohol, alarms and warning lights are activated, the vehicle speed is progressively reduced, and the motor stops within ten to fifteen seconds if the alcohol presence persists. The IR sensor monitors prolonged eye closure, triggering alerts, or automatic vehicle stoppage to prevent accidents caused by drowsiness. Data from the IR sensor is transmitted to a mobile phone via Bluetooth for real-time monitoring and alerts. By identifying driver alcoholism and drowsiness, this system seeks to reduce accidents and save lives by providing safer transportation.

Problem

• Alcohol-impaired driving
• Fatigue driving
• Traffic accidents

Innovation

• Smart Alert System
• Real-time Monitoring
• Alcohol and Fatigue Detection