Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2637064.2637095acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiwwissConference Proceedingsconference-collections
research-article

Help Me!: Valuing and Visualizing Participatory Sensing Tasks with Physical Sensors

Published: 01 September 2014 Publication History

Abstract

Recent progress of mobile devices such as smartphones enables human to leverage their perception ability as a part of sensing framework. This sensing framework, so called participatory sensing, distributes various sensing tasks (e.g., whether report, waiting time in a queue, traffic conditions etc.) to possible participants. Then, participants can select and achieve the sensing tasks. However, in the coming future with the rapid growth of participatory sensing and increasing number of sensing tasks, it must be very hard for users to choose appropriate sensing tasks around them. To solve this problem, we propose a system called Help Me!, which can value and visualize importance of sensing tasks by quantifying them in cooperation with physical sensors. Since Help Me! system provides objective index for sensing tasks, it enhances opportunity for users to participate to sensing tasks. We designed and implemented Help Me! system as an integrated architecture of physical sensors and participatory sensors. Through initial in-lab experiment, we confirmed that Help Me! system can enhance opportunity to participate to sensing tasks for users.

References

[1]
copenhagen wheel project - mit senseable city lab. http://senseable.mit.edu/copenhagenwheel/index.html.
[2]
Sensor andrew. http://sensor.andrew.cmu.edu/users/login.
[3]
Sensor-over-xmpp. http://xmpp.org/extensions/inbox/sensors.html.
[4]
Sun spot world. http://www.sunspotworld.com/.
[5]
Weather news inc. http://weathernews.jp/.
[6]
Xep-0060: Publish-subscribe. http://xmpp.org/extensions/xep-0060.html.
[7]
Xmpp standard foundation. http://xmpp.org/.
[8]
J. A. Burke, D. Estrin, M. Hansen, A. Parker, N. Ramanathan, S. Reddy, and M. B. Srivastava. Participatory sensing. 2006.
[9]
A. T. Campbell, S. B. Eisenman, N. D. Lane, E. Miluzzo, and R. A. Peterson. People-centric urban sensing. In Proceedings of the 2nd annual international workshop on Wireless internet, page 18. ACM, 2006.
[10]
T. Das, P. Mohan, V. N. Padmanabhan, R. Ramjee, and A. Sharma. Prism: platform for remote sensing using smartphones. In Proceedings of the 8th international conference on Mobile systems, applications, and services, pages 63--76. ACM, 2010.
[11]
L. Duan, T. Kubo, K. Sugiyama, J. Huang, T. Hasegawa, and J. Walrand. Incentive mechanisms for smartphone collaboration in data acquisition and distributed computing. In INFOCOM, 2012 Proceedings IEEE, pages 1701--1709. IEEE, 2012.
[12]
S. Kim, J. Mankoff, and E. Paulos. Sensr: evaluating a flexible framework for authoring mobile data-collection tools for citizen science. In Proceedings of the 2013 conference on Computer supported cooperative work, pages 1453--1462. ACM, 2013.
[13]
J.-S. Lee and B. Hoh. Dynamic pricing incentive for participatory sensing. Pervasive and Mobile Computing, 6(6):693--708, 2010.
[14]
Y. Liu, T. Alexandrova, and T. Nakajima. Using stranger as sensors: temporal and geo-sensitive question answering via social media. In Proceedings of the 22nd international conference on World Wide Web, pages 803--814. International World Wide Web Conferences Steering Committee, 2013.
[15]
M.-R. Ra, B. Liu, T. F. La Porta, and R. Govindan. Medusa: A programming framework for crowd-sensing applications. In Proceedings of the 10th international conference on Mobile systems, applications, and services, pages 337--350. ACM, 2012.
[16]
N. Ramanathan, T. Schoellhammer, E. Kohler, K. Whitehouse, T. Harmon, and D. Estrin. Suelo: human-assisted sensing for exploratory soil monitoring studies. In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, pages 197--210. ACM, 2009.
[17]
S. Reddy, D. Estrin, M. Hansen, and M. Srivastava. Examining micro-payments for participatory sensing data collections. In Proceedings of the 12th ACM international conference on Ubiquitous computing, pages 33--36. ACM, 2010.

Cited By

View all
  • (2017)An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-word settingsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.11.001102:C(81-102)Online publication date: 1-Jun-2017

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
IWWISS '14: Proceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing
September 2014
109 pages
ISBN:9781450327473
DOI:10.1145/2637064
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]

In-Cooperation

  • Keio University: Keio University
  • WNRI: Western Norway Research Institute

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2014

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Participatory sensing
  2. XMPP
  3. integrated sensing architecture
  4. mobile sensing
  5. sensor networks
  6. valuing information
  7. visualization of information

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

IWWISS '14

Acceptance Rates

IWWISS '14 Paper Acceptance Rate 12 of 18 submissions, 67%;
Overall Acceptance Rate 12 of 18 submissions, 67%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 23 Dec 2024

Other Metrics

Citations

Cited By

View all
  • (2017)An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-word settingsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.11.001102:C(81-102)Online publication date: 1-Jun-2017

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media