Citation
Foo, Lee Kien and Chua, Sook Ling and Juboor, Saed Sa’deh (2019) Sensor Selection based on Minimum Redundancy Maximum Relevance for Activity Recognition in Smart Homes. In: Computational Science and Technology. Springer, Lecture Notes in Electrical Engineering, pp. 237-247. ISBN 978-981-13-2622-6
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Abstract
Activity recognition in smart homes has attracted increasing attention from researchers due to its potential to recognize the occupant’s activities of daily living such as showering, putting away laundry, grooming, etc. Recognizing the activities of daily living can help to support and assist the older adults, and enable them to continue living independently within their own homes. In order to support the occupants, activity recognition algorithms need to learn from a series of observations obtained from sensors. The central question that this paper aims to address is which sensors are informative for activity recognition. In this paper, the sensor selection problem is addressed using minimum-Redundancy Maximum-Relevance (mRMR) method.
Item Type: | Book Section |
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Uncontrolled Keywords: | Home activity recognition |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics |
Divisions: | Faculty of Computing and Informatics (FCI) |
Depositing User: | Ms Suzilawati Abu Samah |
Date Deposited: | 26 Jan 2022 01:02 |
Last Modified: | 26 Jan 2022 01:02 |
URII: | http://shdl.mmu.edu.my/id/eprint/9007 |
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