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Examining micro-payments for participatory sensing data collections

Authors:

Deborah Estrin,

Mani SrivastavaAuthors Info & Claims

UbiComp '10: Proceedings of the 12th ACM international conference on Ubiquitous computing

Pages 33 - 36

https://doi.org/10.1145/1864349.1864355

Published: 26 September 2010 Publication History

Abstract

The rapid adoption of mobile devices that are able to capture and transmit a wide variety of sensing modalities (media and location) has enabled a new data collection paradigm - participatory sensing. Participatory sensing initiatives organize individuals to gather sensed information using mobile devices through cooperative data collection. A major factor in the success of these data collection projects is sustained, high quality participation. However, since data capture requires a time and energy commitment from individuals, incentives are often introduced to motivate participants. In this work, we investigate the use of micro-payments as an incentive model. We define a set of metrics that can be used to evaluate the effectiveness of incentives and report on findings from a pilot study using various micro-payment schemes in a university campus sustainability initiative.

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Cited By

Jaimes LWhite CAbedin P(2024)Bridging the Gap: An Algorithmic Framework for Vehicular CrowdsensingSensors10.3390/s2422719124:22(7191)Online publication date: 9-Nov-2024
https://doi.org/10.3390/s24227191
Tu CYu ZHan LGuo XHuang FGuo WWang L(2024)Adaptive Budgeting for Collaborative Multi-Task Data Collection in Online Sparse CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2023.334220623:7(7983-7998)Online publication date: Jul-2024
https://doi.org/10.1109/TMC.2023.3342206
Zhou YTong FHe S(2024)Bi-Objective Incentive Mechanism for Mobile Crowdsensing With Budget/Cost ConstraintIEEE Transactions on Mobile Computing10.1109/TMC.2022.322947023:1(223-237)Online publication date: Jan-2024
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Index Terms

Examining micro-payments for participatory sensing data collections
1. Human-centered computing

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Published In

cover image ACM Conferences

UbiComp '10: Proceedings of the 12th ACM international conference on Ubiquitous computing

September 2010

366 pages

ISBN:9781605588438

DOI:10.1145/1864349

General Chairs:
Jakob E. Bardram
IT University of Copenhagen, Denmark
,
Marc Langheinrich
University of Lugano, Switzerland
,
Program Chairs:
Khai N. Truong
University of Toronto, Canada
,
Paddy Nixon
University College Dublin, Ireland

Copyright © 2010 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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University of Florida: University of Florida

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Association for Computing Machinery

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Published: 26 September 2010

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Ubicomp '10

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Ubicomp '10: The 2010 ACM Conference on Ubiquitous Computing

September 26 - 29, 2010

Copenhagen, Denmark

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UbiComp '10 Paper Acceptance Rate 39 of 202 submissions, 19%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Jaimes LWhite CAbedin P(2024)Bridging the Gap: An Algorithmic Framework for Vehicular CrowdsensingSensors10.3390/s2422719124:22(7191)Online publication date: 9-Nov-2024
https://doi.org/10.3390/s24227191
Tu CYu ZHan LGuo XHuang FGuo WWang L(2024)Adaptive Budgeting for Collaborative Multi-Task Data Collection in Online Sparse CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2023.334220623:7(7983-7998)Online publication date: Jul-2024
https://doi.org/10.1109/TMC.2023.3342206
Zhou YTong FHe S(2024)Bi-Objective Incentive Mechanism for Mobile Crowdsensing With Budget/Cost ConstraintIEEE Transactions on Mobile Computing10.1109/TMC.2022.322947023:1(223-237)Online publication date: Jan-2024
https://doi.org/10.1109/TMC.2022.3229470
Liang Y(2024)Crowdsourcing incentive mechanisms for cross-platform tasksEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108008133:PAOnline publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108008
Zhang MLi XMiao YLuo BRen YMa S(2023) PEAK: Privacy-Enhanced Incentive Mechanism for Distributed K -Anonymity in LBS IEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3295451(1-14)Online publication date: 2023
https://doi.org/10.1109/TKDE.2023.3295451
Gosain IGupta AMongia AWahi PJha V(2023)A Survey of Incentive Mechanism in MCS: Types and Characteristics2023 IEEE World AI IoT Congress (AIIoT)10.1109/AIIoT58121.2023.10174500(0613-0619)Online publication date: 7-Jun-2023
https://doi.org/10.1109/AIIoT58121.2023.10174500
Gass JTonkin SMaguin EColder CMahoney MTiffany SHawk L(2023)A preliminary randomized trial of reinforcement contingencies to improve compliance with ecological momentary assessmentTranslational Behavioral Medicine10.1093/tbm/ibad06614:1(60-65)Online publication date: 31-Oct-2023
https://doi.org/10.1093/tbm/ibad066
Suhag DJha V(2023)A comprehensive survey on mobile crowdsensing systemsJournal of Systems Architecture10.1016/j.sysarc.2023.102952142(102952)Online publication date: Sep-2023
https://doi.org/10.1016/j.sysarc.2023.102952
Kimura RNakajima TSatoh I(2023)Gamified CollectiveEyes: A Gamified Distributed Infrastructure for Collectively Sharing People’s EyesProgress in Artificial Intelligence10.1007/978-3-031-49008-8_2(16-28)Online publication date: 15-Dec-2023
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Yi DLi JTang CLin ZHan YQiu R(2022)Task Offloading in Wireless Powered Mobile Crowd Sensing: A Matching-Based ApproachElectronics10.3390/electronics1115237711:15(2377)Online publication date: 30-Jul-2022
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