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Energy-efficient and context-aware smartphone sensor employment

Yürür, Özgür, Liu, Chi Harold, Perera, Charith, Chen, Min, Liu, Xue and Moreno, Wilfrido 2015. Energy-efficient and context-aware smartphone sensor employment. IEEE Transactions on Vehicular Technology 64 (9) , pp. 4230-4244. 10.1109/TVT.2014.2364619

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New-generation mobile devices will inevitably be employed within the realm of ubiquitous sensing. In particular, smartphones have been increasingly used for human activity recognition (HAR)-based studies. It is believed that recognizing human-centric activity patterns could accurately enough give a better understanding of human behaviors. Further, such an ability could have a chance to assist individuals to enhance the quality of their lives. However, the integration and realization of HAR-based mobile services stand as a significant challenge on resourceconstrained mobile-embedded platforms. In this manner, this paper proposes a novel discrete-time inhomogeneous hidden semi-Markov model (DT-IHS-MM)-based generic framework to address a better realization of HAR-based mobile context awareness. In addition, we utilize power-efficient sensor management strategies by providing three intuitive methods and constrained Markov decision process (CMDP), as well as partially observable Markov decision process (POMDP)-based optimal methods. Moreover, a feedback control mechanism is integrated to balance the tradeoff between accuracy in context inference and power consumption. In conclusion, the proposed sensor management methods achieve a 40% overall enhancement in the power consumption caused by the physical sensor with respect to the overall 85–90% accuracy ratio due to the provided adaptive context inference framework.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 0018-9545
Date of First Compliant Deposit: 25 September 2018
Date of Acceptance: 17 October 2014
Last Modified: 11 Mar 2020 10:56

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