State-machine driven opportunistic sensing by mobile devices

Radhika Loomba, Lei Shi, Brendan Jennings

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

2 Citations (Scopus)

Abstract

As mobile devices increasingly incorporate a range of sensors, there is significant potential to apply opportunistic sensing techniques to allow collections of these devices to provide context information to applications. Focussing on a use case involving the use of mobile devices to sense and localize increasing levels of gases in a work environment, we show that the use of application-specific state machines that control the rate at which sensed data is reported, can lead to a significant reduction in battery consumption by the devices in comparison to continuous sensing approaches wherein the reporting rate remains constant.

Original languageEnglish
Title of host publication2014 IEEE Global Communications Conference, GLOBECOM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2739-2744
Number of pages6
ISBN (Electronic)9781479935116
DOIs
Publication statusPublished - 09 Feb 2014
Event2014 IEEE Global Communications Conference, GLOBECOM 2014 - Austin, United States
Duration: 08 Dec 201412 Dec 2014

Publication series

Name2014 IEEE Global Communications Conference, GLOBECOM 2014

Conference

Conference2014 IEEE Global Communications Conference, GLOBECOM 2014
Country/TerritoryUnited States
CityAustin
Period08/12/201412/12/2014

Keywords

  • Context-aware Applications
  • Opportunistic Sensing
  • People-centric Sensing

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