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 |
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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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