Citation

Chua, Sook Ling and Foo, Lee Kien and Juboor, Saed Sa'deh Suleiman (2020) Towards real-time recognition of activities in smart homes. International Journal of Advanced Intelligence Paradigms, 15 (2). pp. 146-164. ISSN 1755-0386

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Abstract

Many supervised methods have been proposed to infer the particular activities of the inhabitants from a variety of sensors attached in the home. Current activity recognition systems either assume that the sensor stream has been presegmented or use a sliding window for activity segmentation. This makes real-time activity recognition task difficult due to the presence of temporal gaps between successive sensor activations. In this paper, we propose a method based on a set of hidden Markov models that can simultaneously solve the problem of activity segmentation and recognition on streaming sensor data without relying on any sliding window methods. We demonstrate our algorithm on sensor data obtained from two publicly available smart homes datasets.

Item Type:	Article
Uncontrolled Keywords:	Human activity recognition, real-time, activity recognition, activity segmentation, streaming data, hidden Markov model, HMM, smart home
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:	16 Dec 2020 14:00
Last Modified:	16 Dec 2020 14:00
URII:	http://shdl.mmu.edu.my/id/eprint/7963

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