Using humans as sensors: An estimation-theoretic perspective

Dong Wang, Md Tanvir Amin, Shen Li, Tarek Abdelzaher, Lance Kaplan, Siyu Gu, Chenji Pan, Hengchang Liu, Charu C. Aggarwal, Raghu Ganti, Xinlei Wang, Prasant Mohapatra, Boleslaw Szymanski, Hieu Le

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

Abstract

The explosive growth in social network content suggests that the largest 'sensor network' yet might be human. Extending the participatory sensing model, this paper explores the prospect of utilizing social networks as sensor networks, which gives rise to an interesting reliable sensing problem. In this problem, individuals are represented by sensors (data sources) who occasionally make observations about the physical world. These observations may be true or false, and hence are viewed as binary claims. The reliable sensing problem is to determine the correctness of reported observations. From a networked sensing standpoint, what makes this sensing problem formulation different is that, in the case of human participants, not only is the reliability of sources usually unknown but also the original data provenance may be uncertain. Individuals may report observations made by others as their own. The contribution of this paper lies in developing a model that considers the impact of such information sharing on the analytical foundations of reliable sensing, and embed it into a tool called Apollo that uses Twitter as a 'sensor network' for observing events in the physical world. Evaluation, using Twitter-based case-studies, shows good correspondence between observations deemed correct by Apollo and ground truth.

Original languageEnglish (US)
Title of host publicationIPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)
PublisherIEEE Computer Society
Pages35-46
Number of pages12
ISBN (Print)9781479931460
DOIs
StatePublished - 2014
Event13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014 - Berlin, Germany
Duration: Apr 15 2014Apr 17 2014

Publication series

NameIPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)

Other

Other13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014
Country/TerritoryGermany
CityBerlin
Period4/15/144/17/14

Keywords

  • data reliability
  • expectation maximization
  • humans as sensors
  • maximum likelihood estimation
  • social sensing
  • uncertain data provenance

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Using humans as sensors: An estimation-theoretic perspective'. Together they form a unique fingerprint.

Cite this