Demo: Distilling likely truth from noisy streaming data with Apollo

Hieu Le, Dong Wang, Hossein Ahmadi, Yusuf S. Uddin, Boleslaw Szymanski, Raghu Ganti, Tarek Abdelzaher, Omid Fatemieh, Hongyang Wang, Jeff Pasternack, Jiawei Han, Dan Roth, Sibel Adali, Hui Lei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

At CPSWeek 2011, the authors presented a demonstration of Apollo, a fact-finder for participatory sensing that ranks archived human-centric and sensor data by credibility. The current demonstration significantly extends our previous work by allowing Apollo to operate on live streaming data; in this case, live Twitter feeds. As the role of humans as sensors increases in emerging sensing applications, a principled approach becomes necessary to address the problem of ascertaining the veracity of sources and observations made by them. Participatory and social sensing applications may use potentially unreliable or unverified sources, such as a phone-based sensing application that grows virally in a large un-vetted population, a disaster-response application, where conflicting damage assessment reports may come from large numbers of different volunteers, or a military application, where friendly observers at a remote location may make hard-to-verify claims about local events. Apollo analyzes noisy data that increasingly plagues human-centric sensing to determine which items of information are more likely to be true.

Original languageEnglish (US)
Title of host publicationSenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Pages417-418
Number of pages2
DOIs
StatePublished - Dec 19 2011
Event9th ACM Conference on Embedded Networked Sensor Systems, SenSys 2011 - Seattle, WA, United States
Duration: Nov 1 2011Nov 4 2011

Publication series

NameSenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems

Other

Other9th ACM Conference on Embedded Networked Sensor Systems, SenSys 2011
CountryUnited States
CitySeattle, WA
Period11/1/1111/4/11

Keywords

  • data fusion
  • participatory sensing
  • quality of information

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Le, H., Wang, D., Ahmadi, H., Uddin, Y. S., Szymanski, B., Ganti, R., Abdelzaher, T., Fatemieh, O., Wang, H., Pasternack, J., Han, J., Roth, D., Adali, S., & Lei, H. (2011). Demo: Distilling likely truth from noisy streaming data with Apollo. In SenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems (pp. 417-418). (SenSys 2011 - Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems). https://doi.org/10.1145/2070942.2071018