• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

MissingFound: An Assistant System for Finding Missing Companions via Mobile Crowdsourcing

Vol. 10, No.10, October 31, 2016
10.3837/tiis.2016.10.008, Download Paper (Free):

Abstract

Looking for missing companions who are out of touch in public places might suffer a long and painful process. With the help of mobile crowdsourcing, the missing person’s location may be reported in a short time. In this paper, we propose MissingFound, an assistant system that applies mobile crowdsourcing for finding missing companions. Discovering valuable users who have chances to see the missing person is the most important task of MissingFound but also a big challenge with the requirements of saving battery and protecting users’ location privacy. A customized metric is designed to measure the probability of seeing, according to users’ movement traces represented by WiFi RSSI fingerprints. Since WiFi RSSI fingerprints provide no knowledge of users’ physical locations, the computation of probability is too complex for practical use. By parallelizing the original sequential algorithms under MapReduce framework, the selecting process can be accomplished within a few minutes for 10 thousand users with records of several days. Experimental evaluation with 23 volunteers shows that MissingFound can select out the potential witnesses in reality and achieves a high accuracy (76.75% on average). We believe that MissingFound can help not only find missing companions, but other public services (e.g., controlling communicable diseases).


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Cite this article

[IEEE Style]
Weiqing Liu, Jing Li, Zhiqiang Zhou and Jiling He, "MissingFound: An Assistant System for Finding Missing Companions via Mobile Crowdsourcing," KSII Transactions on Internet and Information Systems, vol. 10, no. 10, pp. 4766-4786, 2016. DOI: 10.3837/tiis.2016.10.008

[ACM Style]
Liu, W., Li, J., Zhou, Z., and He, J. 2016. MissingFound: An Assistant System for Finding Missing Companions via Mobile Crowdsourcing. KSII Transactions on Internet and Information Systems, 10, 10, (2016), 4766-4786. DOI: 10.3837/tiis.2016.10.008