short-paper

Private Rendezvous-based Calibration of Low-Cost Sensors for Participatory Environmental Sensing

Authors:

Jan-Frederic Markert,

Matthias Budde,

Gregor Schindler,

Michael BeiglAuthors Info & Claims

Urb-IoT '16: Proceedings of the Second International Conference on IoT in Urban Space

Pages 82 - 85

https://doi.org/10.1145/2962735.2962754

Published: 24 May 2016 Publication History

Abstract

Ever-connected smart phones and advanced sensors have lead to new sensing paradigms that promise environmental monitoring in unprecedented spatio-temporal resolution. Especially in air quality sensing with low-cost sensors, regular in-situ device calibration is a helpful approach to ensure data quality. In participatory sensing scenarios, privacy implications arise, as personal sensor data, time and location need to be exchanged. We present a novel privacy-preserving multi-hop sensor calibration scheme that combines Private Proximity Testing and an anonymizing MIX network with cross-sensor calibration based on sensor rendezvous. Our evaluation with simulated ozone measurements and real-world taxicab mobility traces shows that our scheme provides privacy protection while maintaining competitive overall data quality in dense participatory sensing networks.

References

[1]

Balzano, L., and Nowak, R. Blind calibration of sensor networks. In IPSN'07 (2007), ACM, pp. 79--88.

Digital Library

[2]

Budde, M., El Masri, R., Riedel, T., and Beigl, M. Enabling low-cost particulate matter measurement for participatory sensing scenarios. In MUM'13 (2013).

Digital Library

[3]

Budde, M., KÖpke, M., and Beigl, M. Robust in-situ data reconstruction from poisson noise for low-cost, mobile, non-expert environmental sensing. In ISWC'15 (2015).

Digital Library

[4]

Budde, M., Zhang, L., and Beigl, M. Distributed, low-cost particulate matter sensing: scenarios, challenges, approaches. ProScience 1 (2014).

[5]

Bychkovskiy, V., Megerian, S., Estrin, D., and Potkonjak, M. A collaborative approach to In-Place sensor calibration. In IPSN'03. 2003.

Digital Library

[6]

Chaum, D. L. Untraceable electronic mail, return addresses, and digital pseudonyms. Communications of the ACM 24, 2 (1 Feb. 1981), 84--90.

Digital Library

[7]

Christin, D., Reinhardt, A., Kanhere, S. S., and Hollick, M. A survey on privacy in mobile participatory sensing applications. Journal of Systems and Software 84, 11 (2011), 1928--1946.

Digital Library

[8]

Dingledine, R., Mathewson, N., and Syverson, P. Tor: The second-generation onion router. Tech. rep., 2004.

[9]

Hasenfratz, D. Enabling Large-Scale urban air quality monitoring with mobile sensor nodes.

[10]

Hasenfratz, D., Saukh, O., and Thiele, L. On-the-Fly calibration of Low-Cost gas sensors. In Wireless Sensor Networks, vol. 7158 of LNCS. 2012.

Digital Library

[11]

Kazemi, L., and Shahabi, C. Tapas: Trustworthy privacy-aware participatory sensing. Knowledge and information systems 37, 1 (2013), 105--128.

[12]

Kularatna, N., and Sudantha, B. H. An Environmental Air Pollution Monitoring System Based on the IEEE 1451 Standard for Low Cost Requirements. IEEE Sensors 8, 4 (2008).

[13]

Narayanan, A., Thiagarajan, N., Lakhani, M., Hamburg, M., and Boneh, D. Location privacy via private proximity testing. In NDSS (2011).

[14]

Piorkowski, M., Sarafijanovic-Djukic, N., and Grossglauser, M. The epfl/mobility dataset (v. 2009-02-24). http://crawdad.org/epfl/mobility/, 2009.

[15]

Saukh, O., Hasenfratz, D., and Thiele, L. Reducing Multi-Hop calibration errors in Large-Scale mobile sensor networks. In IPSN'15 (2015), ACM.

Digital Library

[16]

Spencer, K. OpenSimplexNoise.java. http://gist.github.com/KdotJPG/b1270127455a94ac5d19, 2014. Accessed 02/25/16.

[17]

Ushida, M., Yamaoka, Y., Itoh, K., and Tsuda, H. New Privacy-Preserving method for matching location data. In IMIS'14 (2014), pp. 594--599.

Digital Library

[18]

Šikšnys, L., Thomsen, J. R., Šaltenis, S., Yiu, M. L., and Andersen, O. A location privacy aware friend locator. In Advances in Spatial and Temporal Databases. 2009.

Digital Library

[19]

WHO. 7 million premature deaths annually linked to air pollution. http://www.who.int/mediacentre/news/releases/2014/air-pollution, 2014. Accessed 02/25/16.

[20]

Wiesner, K., and Dorfmeister, F. PRICAPS: A system for Privacy-Preserving calibration in participatory sensing networks.

[21]

Wiesner, K., Dorfmeister, F., and Linnhoff-Popien, C. Privacy-Preserving calibration for participatory sensing. In Mobiquitous'13, Rev. Sel. Papers. 2014.

[22]

Xiang, Y., Bai, L., Piedrahita, R., Dick, R. P., Lv, Q., Hannigan, M., and Shang, L. Collaborative calibration and sensor placement for mobile sensor networks. In IPSN'12 (2012), ACM, pp. 73--84.

Digital Library

Cited By

Abedi ASanz JSahai A(2024)Using Signals of Opportunity to Establish Trust in Distributed Spectrum Monitoring Systems2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)10.1109/DySPAN60163.2024.10632745(33-38)Online publication date: 13-May-2024
https://doi.org/10.1109/DySPAN60163.2024.10632745
Buelvas JMúnera DTobón V. DAguirre JGaviria N(2023)Data Quality in IoT-Based Air Quality Monitoring Systems: a Systematic Mapping StudyWater, Air, & Soil Pollution10.1007/s11270-023-06127-9234:4Online publication date: 3-Apr-2023
https://doi.org/10.1007/s11270-023-06127-9
Kopackova H(2022)Participatory Citizen Sensing with a Focus on Urban IssuesInternet of Things for Smart Environments10.1007/978-3-031-09729-4_5(71-91)Online publication date: 17-Sep-2022
https://doi.org/10.1007/978-3-031-09729-4_5
Show More Cited By

Recommendations

System-level calibration for data fusion in wireless sensor networks

Wireless sensor networks are typically composed of low-cost sensors that are deeply integrated in physical environments. As a result, the sensing performance of a wireless sensor network is inevitably undermined by biases in imperfect sensor hardware ...
Pre-Deployment Testing, Augmentation and Calibration of Cross-Sensitive Sensors
EWSN '16: Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks

Over the past few years, many low-cost pollution sensors have been integrated into measurement platforms for air quality monitoring. However, using these sensors is challenging: concentrations of toxic substances in ambient air often lie at sensors' ...
Evaluation of a Real, Low Cost, Urban WSN Deployment for Accurate Environmental Monitoring
MASS '11: Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems

There are many areas where Wireless Sensor Networks (WSN) can offer innovative solutions for environmental monitoring applications and the meteorological community, but due to their complexity in terms of energy constraints and low performance devices, ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

Urb-IoT '16: Proceedings of the Second International Conference on IoT in Urban Space

May 2016

122 pages

ISBN:9781450342049

DOI:10.1145/2962735

General Chair:
Takuro Yonezawa
Keio University, Japan

Copyright © 2016 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 the author(s) 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].

In-Cooperation

EAI: The European Alliance for Innovation
SIGAPP: ACM Special Interest Group on Applied Computing
University of Tokyo
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
SIGSPATIAL: ACM Special Interest Group on Spatial Information

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 May 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper
Research
Refereed limited

Conference

Urb-IoT '16

Urb-IoT '16: The Second International Conference on IoT in Urban Space

May 24 - 25, 2016

Tokyo, Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
236
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 25 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Abedi ASanz JSahai A(2024)Using Signals of Opportunity to Establish Trust in Distributed Spectrum Monitoring Systems2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)10.1109/DySPAN60163.2024.10632745(33-38)Online publication date: 13-May-2024
https://doi.org/10.1109/DySPAN60163.2024.10632745
Buelvas JMúnera DTobón V. DAguirre JGaviria N(2023)Data Quality in IoT-Based Air Quality Monitoring Systems: a Systematic Mapping StudyWater, Air, & Soil Pollution10.1007/s11270-023-06127-9234:4Online publication date: 3-Apr-2023
https://doi.org/10.1007/s11270-023-06127-9
Kopackova H(2022)Participatory Citizen Sensing with a Focus on Urban IssuesInternet of Things for Smart Environments10.1007/978-3-031-09729-4_5(71-91)Online publication date: 17-Sep-2022
https://doi.org/10.1007/978-3-031-09729-4_5
Schlund RRiesterer JKöpke MKowalski MTremper PBudde MBeigl M(2021)Calibration of Low-Cost Particulate Matter Sensors with Elastic Weight Consolidation (EWC) as an Incremental Deep Learning MethodScience and Technologies for Smart Cities10.1007/978-3-030-76063-2_40(596-614)Online publication date: 22-May-2021
https://doi.org/10.1007/978-3-030-76063-2_40
Budde M(2021)CrowdsourcingSpringer Handbook of Atmospheric Measurements10.1007/978-3-030-52171-4_44(1207-1239)Online publication date: 2021
https://doi.org/10.1007/978-3-030-52171-4_44
Maag BZhou ZSaukh OThiele L(2017)SCANProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/30900841:2(1-21)Online publication date: 30-Jun-2017
https://dl.acm.org/doi/10.1145/3090084
Budde MÖxler RBeigl MHolopainen JKuramoto IAndo HWallner G(2016)Sensified GamingProceedings of the 13th International Conference on Advances in Computer Entertainment Technology10.1145/3001773.3001832(1-8)Online publication date: 9-Nov-2016
https://dl.acm.org/doi/10.1145/3001773.3001832

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents