research-article

MobiBee: a mobile treasure hunt game for location-dependent fingerprint collection

Authors:

Qiang Xu,

Rong ZhengAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct

Pages 1472 - 1477

https://doi.org/10.1145/2968219.2968590

Published: 12 September 2016 Publication History

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Abstract

Constructing a location-dependent fingerprint map is one of the essential steps for fingerprint-based indoor localization. A comprehensive site survey is time-consuming, labor-intensive, and subjects to environmental changes. In this work, we develop a mobile participatory game, MobiBee, to collect fingerprints with the help of quick response (QR) codes (posted on walls or pillars as location tags). Various incentive strategies, including monetary, entertainment and competition, are utilized. The location marker is deliberately designed to ensure that fingerprints are collected at the targeted locations in a stationary manner. Interestingly, a few instances of QR code forgery have been identified during the game play, which exposes the vulnerability of using QR code in indoor localization. A fraud detection mechanism is hence proposed. Experiments show that the proposed approach can accurately detect the QR code forgery and improve indoor localization accuracy.

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Cited By

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Kraft RBlasi MSchickler MReichert MPryss R(2024)Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical GuidelinesCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-031-54531-3_13(229-248)Online publication date: 23-Feb-2024
https://doi.org/10.1007/978-3-031-54531-3_13
Zhang ETrujillo RTempleton JPoellabauer C(2023)A Study on Mobile Crowd Sensing Systems for Healthcare ScenariosIEEE Access10.1109/ACCESS.2023.334215811(140325-140347)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3342158
Ni JZhang FXiong JHuang QChang ZMa JXie BWang PBian GLi XLiu C(2022)ExperienceProceedings of the 28th Annual International Conference on Mobile Computing And Networking10.1145/3495243.3560546(147-157)Online publication date: 14-Oct-2022
https://dl.acm.org/doi/10.1145/3495243.3560546
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Index Terms

MobiBee: a mobile treasure hunt game for location-dependent fingerprint collection
1. Information systems
  1. Information systems applications

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Published In

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct

September 2016

1807 pages

ISBN:9781450344623

DOI:10.1145/2968219

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
,
Shwetak N. Patel
University of Washington

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Association for Computing Machinery

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Published: 12 September 2016

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UbiComp '16

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UbiComp '16: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 12 - 16, 2016

Germany, Heidelberg

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Kraft RBlasi MSchickler MReichert MPryss R(2024)Operationalizing the Use of Sensor Data in Mobile Crowdsensing: A Systematic Review and Practical GuidelinesCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-031-54531-3_13(229-248)Online publication date: 23-Feb-2024
https://doi.org/10.1007/978-3-031-54531-3_13
Zhang ETrujillo RTempleton JPoellabauer C(2023)A Study on Mobile Crowd Sensing Systems for Healthcare ScenariosIEEE Access10.1109/ACCESS.2023.334215811(140325-140347)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3342158
Ni JZhang FXiong JHuang QChang ZMa JXie BWang PBian GLi XLiu C(2022)ExperienceProceedings of the 28th Annual International Conference on Mobile Computing And Networking10.1145/3495243.3560546(147-157)Online publication date: 14-Oct-2022
https://dl.acm.org/doi/10.1145/3495243.3560546
Sun YDing WShu LLi KZhang YZhou ZHan G(2022)On Enabling Mobile Crowd Sensing for Data Collection in Smart Agriculture: A VisionIEEE Systems Journal10.1109/JSYST.2021.310410716:1(132-143)Online publication date: Mar-2022
https://doi.org/10.1109/JSYST.2021.3104107
Capponi AFiandrino CKantarci BFoschini LKliazovich DBouvry P(2019)A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and OpportunitiesIEEE Communications Surveys & Tutorials10.1109/COMST.2019.291403021:3(2419-2465)Online publication date: Nov-2020
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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
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Guo BLiu YWang LLi VLam JYu Z(2018)Task Allocation in Spatial Crowdsourcing: Current State and Future DirectionsIEEE Internet of Things Journal10.1109/JIOT.2018.28159825:3(1749-1764)Online publication date: Jun-2018
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Ai HHuang WYang YLiao L(2018)The BLE Fingerprint Map Fast Construction Method for Indoor LocalizationAlgorithms and Architectures for Parallel Processing10.1007/978-3-030-05063-4_26(326-340)Online publication date: 7-Dec-2018
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Xu QZheng RTahoun E(2017)Detecting Location Fraud in Indoor Mobile CrowdsensingProceedings of the First ACM Workshop on Mobile Crowdsensing Systems and Applications10.1145/3139243.3139252(44-49)Online publication date: 6-Nov-2017
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Li CXu QGong ZZheng R(2017)TuRF: Fast data collection for fingerprint-based indoor localization2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN)10.1109/IPIN.2017.8115897(1-8)Online publication date: Sep-2017
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Abstract

References

Cited By

Index Terms

Recommendations

Improving indoor positioning precision by using received signal strength fingerprint and footprint based on weighted ambient Wi-Fi signals

Cooperative Target Tracking and Signal Propagation Learning Using Mobile Sensors

Location Fingerprinting Technique for WLAN Device-Free Indoor Localization System

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