research-article

Abnormality Detection Approach using Deep Learning Models in Smart Home Environments

Authors:

A. S. Abdull Sukor,

N. Abdul Rahim,

L. M. Kamarudin,

H. NishizakiAuthors Info & Claims

ICCBN '19: Proceedings of the 7th International Conference on Communications and Broadband Networking

Pages 22 - 27

https://doi.org/10.1145/3330180.3330185

Published: 12 April 2019 Publication History

Abstract

The rising number of elderly populations has become a common concern in many countries. As one of the solutions, smart homes have been developed to help them live independently in their own homes. However, the accurate interpretation in monitoring human situations is still limited. This paper presents an abnormality detection approach that can monitor smart home residents' behavior and identify any abnormalities regarding their daily routines. In particular, this study investigates the use of two deep learning models that are commonly used in the pattern recognition communities, which are known as Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). The learned models are used to classify between normal and abnormal situations and their performance are then compared using a publicly available smart home dataset. Experimental results show that MLP has significant performance and outperforms RNN in terms of accuracy.

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Cited By

Benlala WBouchelaghem SYazid M(2023)Survey on Artificial Intelligence Algorithms Application for Alzheimer’s and Elderly People Safety in Smart HomesAdvanced Computational Techniques for Renewable Energy Systems10.1007/978-3-031-21216-1_42(398-407)Online publication date: 14-Feb-2023
https://doi.org/10.1007/978-3-031-21216-1_42
Sukor ACheik GKamarudin LMao XNishizaki HZakaria ASyed Zakaria S(2022)Predictive Analysis of In-Vehicle Air Quality Monitoring System Using Deep Learning TechniqueAtmosphere10.3390/atmos1310158713:10(1587)Online publication date: 28-Sep-2022
https://doi.org/10.3390/atmos13101587
Widianto MHeryadi YLukas Suparta WWibowo A(2022)Sentiment Analysis of Cooking Oil using Bidirectional Encoder Representations from Transformers2022 5th International Conference on Information and Communications Technology (ICOIACT)10.1109/ICOIACT55506.2022.9971861(110-115)Online publication date: 24-Aug-2022
https://doi.org/10.1109/ICOIACT55506.2022.9971861
Show More Cited By

Index Terms

Abnormality Detection Approach using Deep Learning Models in Smart Home Environments
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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cover image ACM Other conferences

ICCBN '19: Proceedings of the 7th International Conference on Communications and Broadband Networking

April 2019

76 pages

ISBN:9781450362474

DOI:10.1145/3330180

Copyright © 2019 ACM.

© 2019 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

In-Cooperation

UPM: Universiti Putra Malaysia
NITech: Nagoya Institute of Technology
Iv. Javakhishvili Tbilisi State University, Georgia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 April 2019

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ICCBN 2019: 2019 7th International Conference on Communications and Broadband Networking

April 12 - 15, 2019

Nagoya, Japan

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Cited By

Benlala WBouchelaghem SYazid M(2023)Survey on Artificial Intelligence Algorithms Application for Alzheimer’s and Elderly People Safety in Smart HomesAdvanced Computational Techniques for Renewable Energy Systems10.1007/978-3-031-21216-1_42(398-407)Online publication date: 14-Feb-2023
https://doi.org/10.1007/978-3-031-21216-1_42
Sukor ACheik GKamarudin LMao XNishizaki HZakaria ASyed Zakaria S(2022)Predictive Analysis of In-Vehicle Air Quality Monitoring System Using Deep Learning TechniqueAtmosphere10.3390/atmos1310158713:10(1587)Online publication date: 28-Sep-2022
https://doi.org/10.3390/atmos13101587
Widianto MHeryadi YLukas Suparta WWibowo A(2022)Sentiment Analysis of Cooking Oil using Bidirectional Encoder Representations from Transformers2022 5th International Conference on Information and Communications Technology (ICOIACT)10.1109/ICOIACT55506.2022.9971861(110-115)Online publication date: 24-Aug-2022
https://doi.org/10.1109/ICOIACT55506.2022.9971861
Ab Wahab MTay SAbdull Sukor AMohamed AMahinderjit Singh M(2021)Smart Waste Management SystemProceedings of the 12th National Technical Seminar on Unmanned System Technology 202010.1007/978-981-16-2406-3_55(713-724)Online publication date: 25-Sep-2021
https://doi.org/10.1007/978-981-16-2406-3_55

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