research-article

Collaborative opportunistic sensing with mobile phones

Authors:

René NavarroAuthors Info & Claims

UbiComp '14 Adjunct: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication

Pages 1265 - 1272

https://doi.org/10.1145/2638728.2638814

Published: 13 September 2014 Publication History

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Abstract

Mobile phones include a variety of sensors that can be used to develop context-aware applications and gather data about the user's behavior, including the places he visits, his level of activity and how frequently and with whom he socializes. The collection and analysis of these data has been the focus of recent attention in ubiquitous computing, giving rise to the field known as mobile sensing. In this work, we present a collaborative extension to InCense, a toolkit to facilitate behavioral data gathering from populations of mobile phone users. InCense aims at providing people with little or no technical background with a tool that assists in the rapid design and implementation of mobile phone sensing campaigns. By extending the architecture of InCense to support distributed sensing campaigns we are able to incorporate several strategies aimed at optimizing battery, storage, and bandwidth. These issues represent significant challenges in sensing campaigns that generate considerable amounts of data (i.e., collecting audio) or quickly drain the battery in the device (i.e., GPS), given the limitations of mobile devices. In this work, collaborative sensing is used to decide which mobile phone should capture audio when two or more devices are potentially recording a similar audio signal.

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Cited By

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Carvalho LSofia R(2020)A Review on Scaling Mobile Sensing Platforms for Human Activity Recognition: Challenges and Recommendations for Future ResearchIoT10.3390/iot10200251:2(451-473)Online publication date: 29-Nov-2020
https://doi.org/10.3390/iot1020025
Ramos AGarcia-Macias JTentori M(2020)Crowdsensing for Characterizing Mobility and Its Impact on the Subjective Wellbeing in an Underdeveloped RegionApplied Sciences10.3390/app1019668610:19(6686)Online publication date: 24-Sep-2020
https://doi.org/10.3390/app10196686
Groba CSpringer T(2019)Exploring data forwarding with Bluetooth for participatory crowd monitoring2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2019.8730711(71-76)Online publication date: Mar-2019
https://doi.org/10.1109/PERCOMW.2019.8730711
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Index Terms

Collaborative opportunistic sensing with mobile phones
1. Human-centered computing

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Published In

UbiComp '14 Adjunct: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication

September 2014

1409 pages

ISBN:9781450330473

DOI:10.1145/2638728

General Chairs:
AJ Brush
Microsoft Research
,
Adrian Friday
Lancaster University, UK
,
Program Chairs:
Julie Kientz
University of Washington
,
James Scott
Microsoft Research, UK
,
Junehwa Song
Korea Advanced Institute of Science and Technology (KAIST), KR

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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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 September 2014

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UbiComp '14

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UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing

September 13 - 17, 2014

Washington, Seattle

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

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Cited By

View all

Carvalho LSofia R(2020)A Review on Scaling Mobile Sensing Platforms for Human Activity Recognition: Challenges and Recommendations for Future ResearchIoT10.3390/iot10200251:2(451-473)Online publication date: 29-Nov-2020
https://doi.org/10.3390/iot1020025
Ramos AGarcia-Macias JTentori M(2020)Crowdsensing for Characterizing Mobility and Its Impact on the Subjective Wellbeing in an Underdeveloped RegionApplied Sciences10.3390/app1019668610:19(6686)Online publication date: 24-Sep-2020
https://doi.org/10.3390/app10196686
Groba CSpringer T(2019)Exploring data forwarding with Bluetooth for participatory crowd monitoring2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2019.8730711(71-76)Online publication date: Mar-2019
https://doi.org/10.1109/PERCOMW.2019.8730711
Sadhu VZonouz SSritapan VPompili D(2019)HCFContext: Smartphone Context Inference via Sequential History-based Collaborative Filtering2019 IEEE International Conference on Pervasive Computing and Communications (PerCom10.1109/PERCOM.2019.8767396(1-10)Online publication date: Mar-2019
https://doi.org/10.1109/PERCOM.2019.8767396
Mayworm JOliveira JFirmino Fde Farias C(2019)DMEK: Improving Profile Matching in Opportunistic CollaborationsBig Social Data and Urban Computing10.1007/978-3-030-11238-7_11(171-184)Online publication date: 23-Jan-2019
https://doi.org/10.1007/978-3-030-11238-7_11
Navaz ASerhani MAl-Qirim NGergely M(2018)Towards an efficient and Energy-Aware mobile big health data architectureComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2018.10.008166(137-154)Online publication date: Nov-2018
https://doi.org/10.1016/j.cmpb.2018.10.008
Al Hafiz Khan MRoy NSajjad Hossain H(2017)COAR: Collaborative and Opportunistic Human Activity Recognition2017 13th International Conference on Distributed Computing in Sensor Systems (DCOSS)10.1109/DCOSS.2017.16(142-146)Online publication date: Jun-2017
https://doi.org/10.1109/DCOSS.2017.16
Khan MHossain HRoy N(2015)SensePresenceProceedings of the 2015 16th IEEE International Conference on Mobile Data Management - Volume 0210.1109/MDM.2015.41(56-61)Online publication date: 15-Jun-2015
https://dl.acm.org/doi/10.1109/MDM.2015.41

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