Doyle, John and Farrell, Ronan and 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.

Download (116kB)

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:
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

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads