Real-Time Non-Intrusive Driver Fatigue Detection System using Belief Rule-Based Expert System



Mohammad Arfizurrahman1, Ahmad1, Mohammad Shahadat Hossain2,

Mohammad Ahsanul Haque3, and Karl Andersson4+
 

1International Islamic University Chittagong Chittagong, Bangladesh

arfizrahman0@gmail.com, ahmadcse0@gmail.com

2University of Chittagong Chittagong, Bangladesh

hossain_ms@cu.ac.bd

3Radio Analyzer Aalborg, Denmark

iamahsanul@gmail.com

4Luleå University of Technology Skellefteå, Sweden

karl.andersson@ltu.se

 

Abstract

This paper presents a non-intrusive system for detecting driver fatigue in real-time. To determine the level of fatigue the system uses various visual features, namely head nodding, eye closure duration and yawning. A state-of-the-art facial landmark detector ’IntraFace’ has been adopted to determine the eye state, mouth state and head pose estimation. However, different forms of uncertainties such as vagueness, imprecision, ambiguity and incompleteness are involved in calculating these visual parameters. Therefore, a Belief Rule-Based Expert System (BRBES) is employed, which has the ability to handle the uncertainties. The information of the visual parameters is sent to BRBES as input to determine the level of fatigue. An optimal learning model has been developed to improve the performance and accuracy of the BRBES. A comparison between the system and the fuzzy rule based expert system has been carried out. The system generates more effective and reliable results than the fuzzy rule-based expert system.

Keywords: Belief Rule Base, Driver Fatigue, Fatigue Detection, Expert System, Uncertainty

 

+: Corresponding author: Karl Andersson
Pervasive and Mobile Computing and Laboratory, Luleå University of Technology, S-93187 Skellefteå, Sweden,
Tel: +46910585368

 

Journal of Internet Services and Information Security (JISIS), 11(4): 44-60, November 2021
Received: August 17, 2021; Accepted: October 27, 2021; Published: November 30, 2021

DOI: 10.22667/JISIS.2021.11.30.044 [pdf]