Files in this item

FilesDescriptionFormat

application/pdf

application/pdfmain-em-src.pdf (2MB)
(no description provided)PDF

application/pdf

application/pdfmain-em-src.pdf (2MB)
(no description provided)PDF

Description

Title:Using Humans as Sensors: An Estimation-theoretic Perspective
Author(s):Wang, Dong; Amin, Md Tanvir Al; Li, Shen; Kaplan, Lance; Gu, Siyu; Pan, Chenji; Liu, Hengchang; Aggarwal, Charu; Ganti, Raghu K.; Wang, Xinlei; Mohapatra, Prasant; Szymanski,Boleslaw; Le, Hieu; Abdelzaher, Tarek F.
Subject(s):humans as sensors, social sensing, data reliability, uncertain data provenance, maximum likelihood estimation, expectation maximization
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.
Issue Date:2014
Publisher:ACM/IEEE-CS
Citation Info:D. Wang, T. Amin, L. Shen T. ~Abdelzaher, L. Kaplan, et al. Using Humans as Sensors: An Estimation-theoretic Perspective. The 13th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'14), Berlin, Germany, April 2014.
Genre:Conference Paper / Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/47115
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Date Available in IDEALS:2014-02-09


This item appears in the following Collection(s)

Item Statistics