Predicting Activities of Daily Living with Spatio-Temporal Information


Chua, Sook Ling and Foo, Lee Kien and Guesgen, Hans W. (2020) Predicting Activities of Daily Living with Spatio-Temporal Information. Future Internet, 12 (12). pp. 1-13. ISSN 1999-5903

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The smart home has begun playing an important role in supporting independent living by monitoring the activities of daily living, typically for the elderly who live alone. Activity recognition in smart homes has been studied by many researchers with much effort spent on modeling user activities to predict behaviors. Most people, when performing their daily activities, interact with multiple objects both in space and through time. The interactions between user and objects in the home can provide rich contextual information in interpreting human activity. This paper shows the importance of spatial and temporal information for reasoning in smart homes and demonstrates how such information is represented for activity recognition. Evaluation was conducted on three publicly available smart-home datasets. Our method achieved an average recognition accuracy of more than 81% when predicting user activities given the spatial and temporal information.

Item Type: Article
Uncontrolled Keywords: Smart homes
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: 02 Nov 2021 02:21
Last Modified: 02 Nov 2021 02:21


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