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    Extracting Localised Mobile Activity Patterns from Cumulative Mobile Spectrum RSSI


    Doyle, John and Farrell, Ronan and McLoone, Sean F. and McCarthy, Tim and Hung, Peter (2009) Extracting Localised Mobile Activity Patterns from Cumulative Mobile Spectrum RSSI. In: CIICT 2009 : proceedings of the China-Ireland information and communications technologies conference. National University of Ireland, Dept. of Computer Science, Maynooth, Ireland, pp. 75-82. ISBN 9780901519672

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    Abstract

    Techniques for observing the flow of people are creating new means for observing the dynamics between people and the environments they pass through. This ubiquitous connectivity can be observed and interpreted in real-time, through mobile device activity patterns. Recent research into urban analysis through the use of mobile device usage statistics has presented a need for the collection of this data independently from mobile network operators. In this paper we demonstrate that by extracting cumulative received signal strength indication (RSSI) for overall mobile device transmissions, such information can be obtained independently from network operators. We present preliminary results and suggest future applications for which this collection method may be used.

    Item Type: Book Section
    Additional Information: Research presented in this paper was funded by a Strategic Research Cluster grant (07/SRC/ll168) by Science Foundation Ireland under the National Development Plan and by the Irish research Council for Science, Engineering and Technology under their Embark Initiative in partnership with ESRI Ireland. The authors gratefully acknowledge this support.
    Keywords: RSSI; Erlang; human monitoring; geo-temporal weighting;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Institute of Microelectronics and Wireless Systems
    Item ID: 2536
    Depositing User: Sean McLoone
    Date Deposited: 25 May 2011 14:00
    Publisher: National University of Ireland, Dept. of Computer Science
    Refereed: Yes
    Funders: Science Foundation Ireland, Irish research Council for Science, Engineering and Technology
    URI:

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