Driver’s fatigue classification based on physiological signals using RNN-LSTM technique

One of the major reasons for road accidents is driver’s fatigue which causes several fatalities every year. Various studies on road accidents have proved that 20% of the accidents are caused mainly due to fatigue among drivers while driving. This paper presents the use of deep learning technique in classifying fatigue in drivers. By using deep neural networks, features are extracted automatically from preprocessed data of physiological signals such as electrocardiogram, heart rate, skin conductance response and body temperature. Public dataset HciLAB was used to train and validate the classification model. In this work, a comparative analysis of using Recurrent Neural Network - Long Short-term Memory (RNN-LSTM) deep learning architecture and the standard artificial neural network (ANN) was proposed and developed to classify fatigue based on the physiological features of the driver. The results revealed the superiority RNN-LSTM (98%) over standard ANN (80%), for driver fatigue classification. The proposed methods, based on RNN-LSTM deep learning architecture introduced elevated average accuracy in comparison with the standard artificial neural network

Proceedings of International Technical Postgraduate Conference 2022

This conference proceedings contains articles on the various research ideas of the academic & research communities presented at the International Technical Postgraduate Conference 2022 (TECH POST 2022) that was held at Universiti Malaya, Kuala Lumpur, Malaysia on 24-25 September 2022. TECH POST 2022 was organized by the Faculty of Engineering, Universiti Malaya. The theme of the conference is “Embracing Innovative Engineering Technologies Towards a Sustainable Future”.  TECH POST 2022 conference is intended to foster the dissemination of state-of-the-art research from five main disciplines of Engineering: Electrical Engineering, Biomedical Engineering, Civil Engineering, Mechanical Engineering, and Chemical Engineering. The objectives of TECH POST 2022 are to bring together innovative researchers from all engineering disciplines to a common forum, promote R&D activities in Engineering, and promote the dissemination of scientific knowledge and research know-how between researchers, engineers, and students. Conference Title: International Technical Postgraduate Conference 2022Conference Acronym: TECH POST 2022Conference Date: 24-25 September 2022Conference Location: Faculty of Engineering, Universiti Malaya, Kuala Lumpur Malaysia (Hybrid Mode)Conference Organizers: Faculty of Engineering, Universiti Malaya, Kuala Lumpur, Malaysia