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NoiseBay: A Real-World Study on Transparent Data Collection

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Jose RolimAuthors Info & Claims

IC3-2022: Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing

Pages 493 - 501

https://doi.org/10.1145/3549206.3549325

Published: 24 October 2022 Publication History

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Abstract

In applications where data is collected with the help of personal mobile devices, very often, from the user’s point of view, opaque and partly uncontrollable processes are running in the background of devices. In this paper, we show the advantages of an alternative participant-controlled transparent data collection approach. The paper combines a detailed experimental real world study with a best-practice report.

We study the discrepancy between the transparency in the data collection process and the quality of the data collected in the context of mobile crowdsensing (MCS), a paradigm which leverages sensing data from the mobile devices of private individuals. We focus on applications where environmental data is collected and private user data in itself should not have any additional benefit. We treat the concrete example of MCS of tempo-spatial data for the creation of a thematic map of noise levels. We present a lightweight transparent online scheduling approach of opt-in requests for data collection for the users. Within the framework of a real world study, we show that our approach is competitive and results in an improved workload balance among users. We also present data on the responsiveness of users to requests.

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Cited By

Perez-Vereda ACabañero LMoreno NHervas RCanal C(2023)Distributed Crowdsensing Based on Mobile Personal Data StoresProceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023)10.1007/978-3-031-48590-9_1(3-15)Online publication date: 26-Nov-2023
https://doi.org/10.1007/978-3-031-48590-9_1

Index Terms

NoiseBay: A Real-World Study on Transparent Data Collection
1. Human-centered computing
  1. Ubiquitous and mobile computing
2. Information systems
  1. Information retrieval
    1. Users and interactive retrieval

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cover image ACM Other conferences

IC3-2022: Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing

August 2022

710 pages

ISBN:9781450396752

DOI:10.1145/3549206

General Chairs:
Sartaj Sahni
University of Florida, USA
,
Vikas Saxena
JIIT Noida, India
,
Program Chair:
Sundaraja Sitharama Iyengar
Florida International University, USA

Copyright © 2022 ACM.

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New York, NY, United States

Publication History

Published: 24 October 2022

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IC3-2022

IC3-2022: 2022 Fourteenth International Conference on Contemporary Computing

August 4 - 6, 2022

Noida, India

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Cited By

Perez-Vereda ACabañero LMoreno NHervas RCanal C(2023)Distributed Crowdsensing Based on Mobile Personal Data StoresProceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023)10.1007/978-3-031-48590-9_1(3-15)Online publication date: 26-Nov-2023
https://doi.org/10.1007/978-3-031-48590-9_1

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