Real-Time Driver Alert System Using Raspberry Pi

Author:

Wong Jie Yi,Lau Phooi Yee

Abstract

Malaysia has been ranked as one of the country in the world with deadliest road. Based on the statistic, there are around 7000 to 8000 people in the country died on the road among the population of 31 million Malaysians every year. In general, Advances Driver Assistance System (ADAS) aims to improve not only the driving experience but also consider the overall passenger safety. In recent years, driver drowsiness has been one of the major causes of road accidents, which can lead to severe physical injuries, deaths and significant economic losses. In this paper, a vison-based real-time driver alert system aimed mainly to monitor the driver’s drowsiness level and distraction level is proposed. This alert system could reduce the fatalities of car accidents by detecting driver’s face, detecting eyes region using facial landmark and calculating the rate of eyes closure in order to monitor the drowsiness level of the driver. Later, the system is embedded into the Raspberry Pi, with a Raspberry Pi camera and a speaker buzzer, and is used to alert the driver in real-time, by providing a beeping sound. Experimental results show that proposed system is practical and low-cost which could (1) embed the drowsiness detection module, and (2) provide alert notification to the driver when the driver is inattentive, using a medium loud beeping sound, in real-time.

Publisher

ECTI

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploring Subjective Sleepiness with UnnCyberpsy, a Web-Based Psychophysiological Research Tool;Journal on Interactive Systems;2024-09-01

2. Enhancing Road Safety: A System for Detecting Driver Activity Using Raspberry Pi and Computer Vision Techniques with Alcohol and Noise Sensors;Algorithms for Intelligent Systems;2024

3. Driver Assistance Systems with Driver Drowsiness Detection Using Haar-Cascade Algorithm;2023 3rd International Conference on Advancement in Electronics & Communication Engineering (AECE);2023-11-23

4. Driver drowsiness detection and smart alerting using deep learning and IoT;Internet of Things;2023-07

5. Intelligent Driver Monitoring System for Safe Driving;2023 IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC);2023-03-29

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