Drive Sense: An Integrated System for Driver Safety

DOI

10.2991/978-94-6463-471-6_78How to use a DOI?

Keywords

Rectified Linear Unit (ReLU); Convolutional; Neural Network (CNN); Open source Computer Vision (OpenCV); Recurrent Neural Network (RNN); Electroencephalogram (EEG); Electrocardiogram (ECG); Electromyography (EMG)

Abstract

In this paper, we proposed a system which integrates advanced computer vision techniques for enhanced driver safety by emotion recognition and drowsiness recognition. The Global status report on road safety 2023 shows that the number of annual road traffic deaths has fallen slightly to 1.19 million globally. Eye tracking technology monitors blink rate and duration to detect signs of drowsiness. Not only accidents are prone to sleepiness of driver but there may me many ways that the driver is having some mental stress so that there may be chance of happening of accidents. So, our system integrates both physical behaviour and eye status of driver by checking these two parameters we will telling the driving about their state through audio sounds. Deep learning models analye facial expressions to recognize emotions like stress or anger. Personalized things, such as playing soothing music, are used for lowering of stress and enhance the driver's mental state. In proposed system we are using convolutional neural network for emotion recognition as well as drowsy state of driver. By using OpenCV, which is an open-source computer vision concept we are able to capture driver face through live camera and analyses whether driver is in good mental state and also checks drowsiness. If driver is drowsy and having disturbed mindset our system alerts them with sound and by providing some music to enhance their mood and also sends messages to their family. This approach aims to prevent accidents and improve safe journey.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. K. Salma
AU  - P. Padmini Rani
AU  - D. V. S. Madhuri
AU  - B. Rakesh
AU  - B. Gopala Krishna
AU  - B. Ankamma Rao
PY  - 2024
DA  - 2024/07/30
TI  - Drive Sense: An Integrated System for Driver Safety
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 813
EP  - 823
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_78
DO  - 10.2991/978-94-6463-471-6_78
ID  - Salma2024
ER  -