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Multi-resident activity monitoring in smart homes: a case study

Citation

Tran, SN and Zhang, Q and Smallbon, V and Karunanithi, M, Multi-resident activity monitoring in smart homes: a case study, Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, 19-23 March 2018, Athens, Greece, pp. 698-703. ISBN 978-1-5386-3227-7 (2018) [Refereed Conference Paper]

DOI: doi:10.1109/PERCOMW.2018.8480132

Abstract

This paper demonstrates a system that can turn a normal house to a smart house for daily activity monitoring with the use of ambient sensors. We show a proof of concept which includes a method of annotation using voice recording and deep learning technique for automatic recognition. Our multi-resident activity recognition system (MRAR) is designed to support multiple occupants in a house with minimum impact on their living styles. We evaluate the system in a real house lived by a family of three. The experimental results show that it is promising to develop a smart home system for multiple residents which is portable and easy to deploy.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Health
Objective Group:Specific population health (excl. Indigenous health)
Objective Field:Health related to ageing
UTAS Author:Tran, SN (Dr Son Tran)
ID Code:140700
Year Published:2018
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-10-02
Downloads:0

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