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20 November 2024
Reseach Article

An Intelligence System for Taxi-Driver Wellbeing

by Chandrasiri P.Y.K., Ayyash M.A.M., Silva P.C.A., N. Azeem Ahmad, T. Thilakarathne, G. Wimalarathne
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 25
Year of Publication: 2022
Authors: Chandrasiri P.Y.K., Ayyash M.A.M., Silva P.C.A., N. Azeem Ahmad, T. Thilakarathne, G. Wimalarathne
10.5120/ijca2022922305

Chandrasiri P.Y.K., Ayyash M.A.M., Silva P.C.A., N. Azeem Ahmad, T. Thilakarathne, G. Wimalarathne . An Intelligence System for Taxi-Driver Wellbeing. International Journal of Computer Applications. 184, 25 ( Aug 2022), 30-33. DOI=10.5120/ijca2022922305

@article{ 10.5120/ijca2022922305,
author = { Chandrasiri P.Y.K., Ayyash M.A.M., Silva P.C.A., N. Azeem Ahmad, T. Thilakarathne, G. Wimalarathne },
title = { An Intelligence System for Taxi-Driver Wellbeing },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2022 },
volume = { 184 },
number = { 25 },
month = { Aug },
year = { 2022 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number25/32469-2022922305/ },
doi = { 10.5120/ijca2022922305 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:22:23.234033+05:30
%A Chandrasiri P.Y.K.
%A Ayyash M.A.M.
%A Silva P.C.A.
%A N. Azeem Ahmad
%A T. Thilakarathne
%A G. Wimalarathne
%T An Intelligence System for Taxi-Driver Wellbeing
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 25
%P 30-33
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the current development of technology, smart mobile phone is widely used as a method of observing human behavior. With the taxi drivers on roads, the amount of road accidents have also increased. Automation is crucial as the random nature of the above-stated incidents. As the goal of this research, a novel approach, a mobile phone based taxi driver wellbeing monitoring system that is capable of automatically detecting drowsiness, emotional misbehavior and high speed driving is proposed to implement using Machine Learning. This document provides an outline of the proposed system and a summary of outcomes authors have achieved when training appropriate machine learning models to work with real-time data. Systems’ functionality includes identifying human sleepy eyes, irrational emotions and high speed using the mobile device.

References
  1. TensorFlow Wikipedia
  2. Hong, J.-H. a. (2014). A smartphone-based sensing platform to model aggressive driving behaviors.
  3. Johnson, D. A. (2011). Driving style recognition using a smartphone as a sensor platform. In 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) (pp. 1609--1615).
  4. Zeeman, A.S. and Booysen, M.J., 2013, October. Combining speed and acceleration to detect reckless driving in the informal public transport industry. In 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) (pp. 756-761). IEEE.
  5. Akhtar, N., Pandey, K. and Gupta, S., 2014, April. Mobile application for safe driving. In 2014 Fourth International Conference on Communication Systems and Network Technologies (pp. 212-216). IEEE.
  6. https://teachablemachine.withgoogle.com/train
  7. https://api.flutter.dev/flutter/painting/ImageStream-class.html
  8. https://www.tensorflow.org/lite
  9. https://api.flutter.dev/flutter/widgets/CustomPaint-class.html
Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning drowsiness detection emotion detection mask detection taxy