Presumably Simple: Monitoring Crowds Using WiFi

Cristian Chilipirea, Andreaa Petre, Ciprian Dobre, Maarten van Steen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    19 Citations (Scopus)
    61 Downloads (Pure)

    Abstract

    Crowd Monitoring is receiving much attention. An increasingly popular technique is to scan for mobile devices, notably smartphones. We take a look at scanning for such devices by recording WiFi packets. Although research on capturing crowd patterns using WiFi detections has been done, there are not many published results when it comes to tracking movements. This is not surprising when realizing that the data provided by WiFi scanners is susceptible to many seemingly erroneous and missed detections, caused by the use of randomized network addresses, overlap between scanners, high variance in WiFi detection ranges, among other sources. In this paper, we investigate various techniques for cleaning up sets of raw detections to sets that can subsequently be used for crowd analytics. To this end, we introduce two different quality metrics to measure the effects of applying the various techniques. We test our approach using a data set collected from 27 WiFi scanners spread across the downtown area of a Dutch city where at that time a 3-day multi-stage festival took place attended by some 130,000 people.
    Original languageEnglish
    Title of host publication2016 17th International Conference on Mobile Data Management (MDM)
    PublisherIEEE
    ISBN (Electronic)978-1-5090-0883-4
    DOIs
    Publication statusPublished - 2016
    Event17th IEEE International Conference on Mobile Data Management 2016 - Porto, Portugal
    Duration: 13 Jun 201616 Jun 2016
    Conference number: 17
    http://mdmconferences.org/mdm2016/

    Conference

    Conference17th IEEE International Conference on Mobile Data Management 2016
    Abbreviated titleMDM 2016
    CountryPortugal
    CityPorto
    Period13/06/1616/06/16
    Internet address

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