research-article

History-based Incentive for Crowd Sensing

Authors:

Tomoya Tsujimori,

Niwat Thepvilojanapong,

Yoshikatsu Ohta,

Yoshito TobeAuthors Info & Claims

IWWISS '14: Proceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing

Pages 1 - 6

https://doi.org/10.1145/2637064.2637089

Published: 01 September 2014 Publication History

Abstract

An increasing popularity of smartphones affects interaction behaviors between people. The ubiquity of smartphones with embedded sensors can enable attractive sensing applications for collecting and reporting data in participatory sensing environment. However, time and monetary cost hinder people from providing sensing data using their smartphones. Smartphone users will probably not participate in sensing tasks without incentive in the real world. Therefore, we propose SenseUtil which provides participation-aware incentive for crowd sensing environment. The main objective of SenseUtil is to keep moderate payment. SenseUtil applies the concept of microeconomics, where demand and supply determine the value of sensed data. Several factors including sensing frequency, nearby sensing points and users' preference, affect the incentive which dynamically changes over time. We implemented a simulation to study the impact of participation-aware incentive mechanisms. The results demonstrate that historical data of participation activities help decrease payments moderately.

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Cited By

Chen X(2024)Maximizing the Total Utility of Requesters in Crowdsourcing2024 10th IEEE International Conference on High Performance and Smart Computing (HPSC)10.1109/HPSC62738.2024.00008(1-6)Online publication date: 10-May-2024
https://doi.org/10.1109/HPSC62738.2024.00008
Li SShen WBilal MXu XDou WMoustafa N(2022)Fair and size-scalable participant selection framework for large-scale mobile crowdsensingJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2021.102273119:COnline publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1016/j.sysarc.2021.102273
Dasari VKantarci BSimsek M(2019)Trustworthiness and Comfort-Aware Participant Recruitment for Mobile Crowd-Sensing in Smart Environments2019 IEEE Symposium on Computers and Communications (ISCC)10.1109/ISCC47284.2019.8969704(1-6)Online publication date: Jun-2019
https://doi.org/10.1109/ISCC47284.2019.8969704
Show More Cited By

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History-based Incentive for Crowd Sensing

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Published In

cover image ACM Other conferences

IWWISS '14: Proceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing

September 2014

109 pages

ISBN:9781450327473

DOI:10.1145/2637064

Editors:
Pierre Maret,
Satoshi Honda,
Program Chairs:
Rajendra Akerkar
Western Norway Research Institute, Norway
,
Fuyuki Ishikawa
National Institute of Informatics, Japan
,
Takuro Yonezawa
Keio University, Japan
,
Till Riedel
University of Karlsruhe, Germany
,
Publications Chair:
Martin Alexander Neumann
University of Karlsruhe, Germany

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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Keio University: Keio University
WNRI: Western Norway Research Institute

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2014

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IWWISS '14

IWWISS '14: International Workshop on Web Intelligence and Smart Sensing

September 1 - 2, 2014

Saint Etienne, France

Acceptance Rates

IWWISS '14 Paper Acceptance Rate 12 of 18 submissions, 67%;

Overall Acceptance Rate 12 of 18 submissions, 67%

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Cited By

Chen X(2024)Maximizing the Total Utility of Requesters in Crowdsourcing2024 10th IEEE International Conference on High Performance and Smart Computing (HPSC)10.1109/HPSC62738.2024.00008(1-6)Online publication date: 10-May-2024
https://doi.org/10.1109/HPSC62738.2024.00008
Li SShen WBilal MXu XDou WMoustafa N(2022)Fair and size-scalable participant selection framework for large-scale mobile crowdsensingJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2021.102273119:COnline publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1016/j.sysarc.2021.102273
Dasari VKantarci BSimsek M(2019)Trustworthiness and Comfort-Aware Participant Recruitment for Mobile Crowd-Sensing in Smart Environments2019 IEEE Symposium on Computers and Communications (ISCC)10.1109/ISCC47284.2019.8969704(1-6)Online publication date: Jun-2019
https://doi.org/10.1109/ISCC47284.2019.8969704
Liu YKong LChen G(2019)Data-Oriented Mobile Crowdsensing: A Comprehensive SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2019.291085521:3(2849-2885)Online publication date: Nov-2020
https://doi.org/10.1109/COMST.2019.2910855
Connolly MDusparic IIosifidis GBouroche M(2018)Adaptive Reward Allocation for Participatory SensingWireless Communications & Mobile Computing10.1155/2018/63534252018Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1155/2018/6353425
Leppänen TÁlvarez Lacasia JTobe YSezaki KRiekki J(2017)Mobile crowdsensing with mobile agentsAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9311-731:1(1-35)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1007/s10458-015-9311-7
Ogie R(2016)Adopting incentive mechanisms for large-scale participation in mobile crowdsensingHuman-centric Computing and Information Sciences10.1186/s13673-016-0080-36:1(1-31)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1186/s13673-016-0080-3
Oide TAbe TSuganuma T(2016)A broker-less participatory sensing scheme by user matching mechanism based on market price approach2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)10.1109/PERCOMW.2016.7457104(1-6)Online publication date: Mar-2016
https://doi.org/10.1109/PERCOMW.2016.7457104
Tobe YUsami IKobana YTakahashi JLopez GThepvilojanapong N(2014)vCity Map: Crowdsensing towards visible citiesIEEE SENSORS 2014 Proceedings10.1109/ICSENS.2014.6984921(17-20)Online publication date: Nov-2014
https://doi.org/10.1109/ICSENS.2014.6984921

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