research-article

Mood-fatigue analyzer: towards context-aware mobile sensing applications for safe driving

Authors:

Georgios Fotopoulos,

Edith C.-H. Ngai,

Victor C. M. LeungAuthors Info & Claims

M4IOT '14: Proceedings of the 1st ACM Workshop on Middleware for Context-Aware Applications in the IoT

Pages 19 - 24

https://doi.org/10.1145/2676743.2676747

Published: 09 December 2014 Publication History

Abstract

Nowadays more and more organizations focus on reducing traffic accidents and defensive measures for safe driving. The vigilance level (e.g., negative emotion and fatigue) also accounts for the road injuries. Till now, there is no systematic solution for different mobile devices that can effectively infer the mood and fatigue of drivers in real-time or conveniently be used by drivers, nor incentive scheme for drivers in large scale to stimulate their positive and secure driving collaboratively with friends in a social context. In this paper, we propose the Mood-Fatigue Analyzer (MFA), a systematic solution that can be used in different middlewares on mobile devices, which can transform the data from sensors to context-aware mobile sensing applications for safe driving. The MFA employs multidimensional methods to get the drivers' real-time mood and fatigue information by sensors using the Internet of Things (IoT) deployed in and out of cars. Besides promoting safe driving with integrated sensors, the MFA could be built on a multi-tier vehicular social network (VSN) platform, which enables communication among drivers in a social context via cloud platform. Architecture implementation and experimental results of the MFA have demonstrated its desired functionalities and efficiency in drivers' daily lives and real-world deployment.

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Cited By

Banotra AGhose SMishra DModem S(2023)Energy harvesting in self-sustainable IoT devices and applications based on cross-layer architecture design: A surveyComputer Networks10.1016/j.comnet.2023.110011236(110011)Online publication date: Nov-2023
https://doi.org/10.1016/j.comnet.2023.110011
Maulid HNurhidayat WPriyono S(2020)SafeDri: A mobile-based application for safety drivingIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/850/1/012003850(012003)Online publication date: 23-May-2020
https://doi.org/10.1088/1757-899X/850/1/012003
Sethi PSarangi S(2017)Internet of ThingsJournal of Electrical and Computer Engineering10.1155/2017/93240352017(6)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1155/2017/9324035
Show More Cited By

Index Terms

Mood-fatigue analyzer: towards context-aware mobile sensing applications for safe driving
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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cover image ACM Other conferences

M4IOT '14: Proceedings of the 1st ACM Workshop on Middleware for Context-Aware Applications in the IoT

December 2014

36 pages

ISBN:9781450332347

DOI:10.1145/2676743

Conference Chairs:
Danny Hughes
Leuven University, Belgium
,
Chantal Taconet
Télécom SudParis, France
,
Sébastien Leriche
ENAC - University of Toulouse, France

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 December 2014

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Middleware '14

Middleware '14: 15th International Middleware Conference

December 9, 2014

Bordeaux, France

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M4IOT '14 Paper Acceptance Rate 5 of 10 submissions, 50%;

Overall Acceptance Rate 10 of 18 submissions, 56%

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Cited By

Banotra AGhose SMishra DModem S(2023)Energy harvesting in self-sustainable IoT devices and applications based on cross-layer architecture design: A surveyComputer Networks10.1016/j.comnet.2023.110011236(110011)Online publication date: Nov-2023
https://doi.org/10.1016/j.comnet.2023.110011
Maulid HNurhidayat WPriyono S(2020)SafeDri: A mobile-based application for safety drivingIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/850/1/012003850(012003)Online publication date: 23-May-2020
https://doi.org/10.1088/1757-899X/850/1/012003
Sethi PSarangi S(2017)Internet of ThingsJournal of Electrical and Computer Engineering10.1155/2017/93240352017(6)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1155/2017/9324035
Vahdat-Nejad HIzadpanah SOstadi-Eilaki S(2017)Context-aware cloud-based systems: design aspectsCluster Computing10.1007/s10586-017-1425-zOnline publication date: 4-Dec-2017
https://doi.org/10.1007/s10586-017-1425-z
Tu WWei LHu WSheng ZNicanfar HHu XNgai ELeung V(2016)A Survey on Mobile Sensing Based Mood-Fatigue Detection for DriversSmart City 360°10.1007/978-3-319-33681-7_1(3-15)Online publication date: 29-Jun-2016
https://doi.org/10.1007/978-3-319-33681-7_1
Huo YTu WSheng ZLeung V(2015)A survey of in-vehicle communicationsProceedings of the 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT)10.1109/WF-IoT.2015.7389040(132-137)Online publication date: 14-Dec-2015
https://dl.acm.org/doi/10.1109/WF-IoT.2015.7389040

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