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    Utilising Mobile Phone RSSI Metric for Human Activity Detection


    Doyle, John, Farrell, Ronan, McLoone, Sean F. and McCarthy, Tim (2009) Utilising Mobile Phone RSSI Metric for Human Activity Detection. Signals and Systems Conference (ISSC 2009) IET. pp. 1-6.

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    Abstract

    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 propose that cumulative received signal strength indications (RSSI) for overall mobile device transmissions in an area may provide such independent information. A process for the detection of high density areas within the RSSI temporal data set will be demonstrated. Finally, future applications for this collection method are discussed and we highlight its potential to complement traditional metric analysis techniques, for the representation of intensity of urban and local activities and their evolution through time and space.
    Item Type: Article
    Keywords: Mobile communications; RSSI; Erlang; urban analysis; human activity; geographical mapping; temporal analysis;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 2322
    Depositing User: Sean McLoone
    Date Deposited: 11 Jan 2011 14:26
    Journal or Publication Title: Signals and Systems Conference (ISSC 2009) IET
    Publisher: IEEE
    Refereed: Yes
    URI: https://mural.maynoothuniversity.ie/id/eprint/2322
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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