research-article

PRISM: platform for remote sensing using smartphones

Authors:

Prashanth Mohan,

Venkata N. Padmanabhan,

Ramachandran Ramjee,

Asankhaya SharmaAuthors Info & Claims

MobiSys '10: Proceedings of the 8th international conference on Mobile systems, applications, and services

Pages 63 - 76

https://doi.org/10.1145/1814433.1814442

Published: 15 June 2010 Publication History

Abstract

To realize the potential of opportunistic and participatory sensing using mobile smartphones, a key challenge is ensuring the ease of developing and deploying such applications, without the need for the application writer to reinvent the wheel each time. To this end, we present a Platform for Remote Sensing using Smartphones (PRISM) that balances the interconnected goals of generality, security, and scalability. PRISM allows application writers to package their applications as executable binaries, which offers efficiency and also the flexibility of reusing existing code modules. PRISM then pushes the application out automatically to an appropriate set of phones based on a specified set of predicates. This push model enables timely and scalable application deployment while still ensuring a good degree of privacy. To safely execute untrusted applications on the smartphones, while allowing them controlled access to sensitive sensor data, we augment standard software sandboxing with several PRISM-specific elements like resource metering and forced amnesia.

We present three applications built on our implementation of PRISM on Windows Mobile: citizen journalist, party thermometer, and road bump monitor. These applications vary in the set of sensors they use and in their mode of operation (depending on human input vs. automatic). We report on our experience from a small-scale deployment of these applications. We also present a large-scale simulation-based analysis of the scalability of PRISM's push model.

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Cited By

Chen WXu XRen NZhu CCai J(2025)Copyright Verification and Traceability for Remote Sensing Object Detection Models via Dual Model WatermarkingRemote Sensing10.3390/rs1703048117:3(481)Online publication date: 30-Jan-2025
https://doi.org/10.3390/rs17030481
Yu ZZhao LCui HSong YLiu YLuo YGuo B(2024)CrowdKit: A Generic Programming Framework for Mobile Crowdsensing ApplicationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.338157823:11(10584-10597)Online publication date: Nov-2024
https://doi.org/10.1109/TMC.2024.3381578
Al-Shaery AAhmed SAljassmi HAl-Hawsawi AMaksoud NTridane AFarooqi N(2024)Open Dataset for Predicting Pilgrim Activities for Crowd Management During Hajj Using Wearable SensorsIEEE Access10.1109/ACCESS.2024.340223012(72828-72846)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3402230
Show More Cited By

Index Terms

PRISM: platform for remote sensing using smartphones
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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Published In

cover image ACM Conferences

MobiSys '10: Proceedings of the 8th international conference on Mobile systems, applications, and services

June 2010

382 pages

ISBN:9781605589855

DOI:10.1145/1814433

General Chair:
Sujata Banerjee
Hewlett-Packard Labs., USA
,
Program Chairs:
Srinivasan Keshav
University of Waterloo, Ontario, Canada
,
Alec Wolman
Microsoft Research Redmond, USA

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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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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New York, NY, United States

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Published: 15 June 2010

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MobiSys'10

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SIGMOBILE

MobiSys'10: The 8th International Conference on Mobile Systems, Applications, and Services

June 15 - 18, 2010

California, San Francisco, USA

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Cited By

Chen WXu XRen NZhu CCai J(2025)Copyright Verification and Traceability for Remote Sensing Object Detection Models via Dual Model WatermarkingRemote Sensing10.3390/rs1703048117:3(481)Online publication date: 30-Jan-2025
https://doi.org/10.3390/rs17030481
Yu ZZhao LCui HSong YLiu YLuo YGuo B(2024)CrowdKit: A Generic Programming Framework for Mobile Crowdsensing ApplicationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.338157823:11(10584-10597)Online publication date: Nov-2024
https://doi.org/10.1109/TMC.2024.3381578
Al-Shaery AAhmed SAljassmi HAl-Hawsawi AMaksoud NTridane AFarooqi N(2024)Open Dataset for Predicting Pilgrim Activities for Crowd Management During Hajj Using Wearable SensorsIEEE Access10.1109/ACCESS.2024.340223012(72828-72846)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3402230
Ma PGarg SBarika M(2024)Research allocation in mobile volunteer computing system: Taxonomy, challenges and future workFuture Generation Computer Systems10.1016/j.future.2024.01.015154(251-265)Online publication date: May-2024
https://doi.org/10.1016/j.future.2024.01.015
Kumar A(2024)Pavement surface condition assessment: a-state-of-the-art research review and future perspectiveInnovative Infrastructure Solutions10.1007/s41062-024-01755-49:12Online publication date: 13-Nov-2024
https://doi.org/10.1007/s41062-024-01755-4
Yang GGuo DWang BHe XWang JWang G(2023)Participant-Quantity-Aware Online Task Allocation in Mobile CrowdsensingIEEE Internet of Things Journal10.1109/JIOT.2023.330503410:24(22650-22663)Online publication date: 15-Dec-2023
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Li ZTan ZLong SLi CWang PDeng Q(2023)A novel coverage-aware task allocation scheme in Cooperative Mobile Crowd SensingAd Hoc Networks10.1016/j.adhoc.2023.103297151(103297)Online publication date: Dec-2023
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Ang KSeng JNgharamike E(2022)Towards Crowdsourcing Internet of Things (Crowd-IoT): Architectures, Security and ApplicationsFuture Internet10.3390/fi1402004914:2(49)Online publication date: 31-Jan-2022
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Mathew SEl Barachi MKuhail M(2022)CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident ReportingApplied Sciences10.3390/app12211115612:21(11156)Online publication date: 3-Nov-2022
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Tan WLiu JLiang ZDing K(2022)Based on Bid and Data Quality Incentive Mechanisms for Mobile Crowd Sensing Systems2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD54268.2022.9776098(89-94)Online publication date: 4-May-2022
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