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IoT Based Public Transportation Accident Prevention with Driver Alcohol Detection and Smoke System

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  • Ayobami O. Adedokun

    (Department of Computer Engineering, Federal University of Technology PMB 704, Akure, Ondo State, Nigeria)

Abstract

In Nigeria, 1,834 deaths were recorded from 3,345 road accidents between January and March 2022, according to the National Bureau of Statistics (NBS), underscoring the critical need for improved road safety measures. This study proposes an IoT-based system designed to prevent accidents in public transportation by addressing two major risk factors: alcohol-impaired driving and smoking while driving. The system utilizes MQ3 and MQ2 sensors for alcohol and smoke detection, respectively, which are installed within the vehicle interior. These sensors are connected to a central control unit that processes data in real-time. Upon detection of alcohol or smoke, the system triggers visual and auditory alerts, deactivates the vehicle’s engine, and sends notifications to the relevant transportation authority. The architecture of the system ensures seamless data communication, allowing for remote monitoring and control. The findings demonstrate the potential of IoT-driven solutions in reducing road accidents and underscore the importance of integrating sensor technology, real-time data processing, and wireless communication for next-generation accident prevention.

Suggested Citation

  • Ayobami O. Adedokun, 2024. "IoT Based Public Transportation Accident Prevention with Driver Alcohol Detection and Smoke System," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(8), pages 765-775, August.
    • Handle: RePEc:bjf:journl:v:9:y:2024:i:8:p:765-775
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