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
|
Abstract
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 |
URI: |
http://orca.cf.ac.uk/id/eprint/114933 |
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