research-article

Energy-Efficient Localization and Tracking on Smartphones: Design Principle and Solutions

Authors:

Athanasios V. VasilakosAuthors Info & Claims

CFI '16: Proceedings of the 11th International Conference on Future Internet Technologies

Pages 29 - 35

https://doi.org/10.1145/2935663.2935675

Published: 15 June 2016 Publication History

Abstract

In recent years, various location based services (LBS) have witnessed great development and are being prevalently used in our life. However, as the foundation of various LBS applications, localization consumes large energy of resource-constraint mobile terminals, especially on smartphones. This paper explicitly proposes three technical principles, substitution, adaption and collaboration to guide energy-efficient localization and tracking schemes on smartphones. Then several typical schemes in indoor or outdoor environments are respectively summarized and compared under the umbrella of those three principles. Moreover, the context-assisting techniques are also discussed to design energy-efficient LBS applications. Finally, the quantitative metrics to measure the tradeoff between energy and localization performance are summarized. The primary goal of this paper is to comprehensively classify and provide a summary on the sporadic localization schemes (with energy-efficiency as main concern), possible solutions and tradeoffs, and facilitate to develop and deploy the energy-efficient LBS applications.

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Cited By

Tiku SPasricha S(2023)An Overview of Indoor Localization TechniquesMachine Learning for Indoor Localization and Navigation10.1007/978-3-031-26712-3_1(3-25)Online publication date: 30-Jun-2023
https://doi.org/10.1007/978-3-031-26712-3_1
Langlois CTiku SPasricha S(2017)Indoor Localization with Smartphones: Harnessing the Sensor Suite in Your PocketIEEE Consumer Electronics Magazine10.1109/MCE.2017.27147196:4(70-80)Online publication date: Oct-2017
https://doi.org/10.1109/MCE.2017.2714719

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cover image ACM Other conferences

CFI '16: Proceedings of the 11th International Conference on Future Internet Technologies

June 2016

126 pages

ISBN:9781450341813

DOI:10.1145/2935663

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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AsiaFI: Asia Future Internet

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 June 2016

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CFI '16

CFI '16: The 11th International Conference on Future Internet Technologies

June 15 - 17, 2016

Nanjing, China

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Overall Acceptance Rate 29 of 55 submissions, 53%

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Cited By

Tiku SPasricha S(2023)An Overview of Indoor Localization TechniquesMachine Learning for Indoor Localization and Navigation10.1007/978-3-031-26712-3_1(3-25)Online publication date: 30-Jun-2023
https://doi.org/10.1007/978-3-031-26712-3_1
Langlois CTiku SPasricha S(2017)Indoor Localization with Smartphones: Harnessing the Sensor Suite in Your PocketIEEE Consumer Electronics Magazine10.1109/MCE.2017.27147196:4(70-80)Online publication date: Oct-2017
https://doi.org/10.1109/MCE.2017.2714719

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