Research Article
An Intelligence System for Taxi-Driver Wellbeing
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 184 - Issue 25 |
| Published: Aug 2022 |
| Authors: Chandrasiri P.Y.K., Ayyash M.A.M., Silva P.C.A., N. Azeem Ahmad, T. Thilakarathne, G. Wimalarathne |
10.5120/ijca2022922305
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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 },
year = { 2022 },
volume = { 184 },
number = { 25 },
pages = { 30-33 },
doi = { 10.5120/ijca2022922305 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2022
%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%T
%J International Journal of Computer Applications
%V 184
%N 25
%P 30-33
%R 10.5120/ijca2022922305
%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
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- 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.
- 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.
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Index Terms
Keywords