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An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets

Internet of Things (IoT) technology has been rapidly developing and has been well utilized in the field of smart city monitoring. The IoT offers new opportunities for cities to use data remotely for the monitoring, smart management, and control of device mechanisms that enable the processing of larg...

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Main Authors: Khalifa, Othman Omran, Roubleh, Adil, Esgiar, Abdelrahim N., Abdelhaq, Maha, Alsaqour, Raed A., Hassan Abdalla Hashim, Aisha, Sayed Ali, Elmustafa, Saeed, Rashid
Format: Article
Language:English
Published: Multidisciplinary Digital Publishing Institute (MDPI) 2022
Subjects:
T Technology (General)
T10.5 Communication of technical information
Online Access:http://irep.iium.edu.my/100377/7/100377_An%20IoT-platform-based%20deep%20learning%20system.pdf
http://irep.iium.edu.my/100377/
https://www.mdpi.com/2079-8954/10/5/177/pdf?version=1664626799
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spelling my.iium.irep.1003772022-10-03T02:11:58Z http://irep.iium.edu.my/100377/ An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets Khalifa, Othman Omran Roubleh, Adil Esgiar, Abdelrahim N. Abdelhaq, Maha Alsaqour, Raed A. Hassan Abdalla Hashim, Aisha Sayed Ali, Elmustafa Saeed, Rashid T Technology (General) T10.5 Communication of technical information Internet of Things (IoT) technology has been rapidly developing and has been well utilized in the field of smart city monitoring. The IoT offers new opportunities for cities to use data remotely for the monitoring, smart management, and control of device mechanisms that enable the processing of large volumes of data in real time. The IoT supports the connection of instruments with intelligible features in smart cities. However, there are some challenges due to the ongoing development of these applications. Therefore, there is an urgent need for more research from academia and industry to obtain citizen satisfaction, and efficient architecture, protocols, security, and services are required to fulfill these needs. In this paper, the key aspects of an IoT infrastructure for smart cities were analyzed. We focused on citizen behavior recognition using convolution neural networks (CNNs). A new model was built on understanding human behavior by using the berkeley multimodal human action (MHAD) Datasets. A video surveillance system using CNNs was implemented. The proposed model’s simulation results achieved 98% accuracy for the citizen behavior recognition system. Multidisciplinary Digital Publishing Institute (MDPI) 2022-10-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/100377/7/100377_An%20IoT-platform-based%20deep%20learning%20system.pdf Khalifa, Othman Omran and Roubleh, Adil and Esgiar, Abdelrahim N. and Abdelhaq, Maha and Alsaqour, Raed A. and Hassan Abdalla Hashim, Aisha and Sayed Ali, Elmustafa and Saeed, Rashid (2022) An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets. Systems, 10 (5). pp. 1-17. E-ISSN 2079-8954 https://www.mdpi.com/2079-8954/10/5/177/pdf?version=1664626799
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic T Technology (General)
T10.5 Communication of technical information
spellingShingle T Technology (General)
T10.5 Communication of technical information
Khalifa, Othman Omran
Roubleh, Adil
Esgiar, Abdelrahim N.
Abdelhaq, Maha
Alsaqour, Raed A.
Hassan Abdalla Hashim, Aisha
Sayed Ali, Elmustafa
Saeed, Rashid
An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
description Internet of Things (IoT) technology has been rapidly developing and has been well utilized in the field of smart city monitoring. The IoT offers new opportunities for cities to use data remotely for the monitoring, smart management, and control of device mechanisms that enable the processing of large volumes of data in real time. The IoT supports the connection of instruments with intelligible features in smart cities. However, there are some challenges due to the ongoing development of these applications. Therefore, there is an urgent need for more research from academia and industry to obtain citizen satisfaction, and efficient architecture, protocols, security, and services are required to fulfill these needs. In this paper, the key aspects of an IoT infrastructure for smart cities were analyzed. We focused on citizen behavior recognition using convolution neural networks (CNNs). A new model was built on understanding human behavior by using the berkeley multimodal human action (MHAD) Datasets. A video surveillance system using CNNs was implemented. The proposed model’s simulation results achieved 98% accuracy for the citizen behavior recognition system.
format Article
author Khalifa, Othman Omran
Roubleh, Adil
Esgiar, Abdelrahim N.
Abdelhaq, Maha
Alsaqour, Raed A.
Hassan Abdalla Hashim, Aisha
Sayed Ali, Elmustafa
Saeed, Rashid
author_facet Khalifa, Othman Omran
Roubleh, Adil
Esgiar, Abdelrahim N.
Abdelhaq, Maha
Alsaqour, Raed A.
Hassan Abdalla Hashim, Aisha
Sayed Ali, Elmustafa
Saeed, Rashid
author_sort Khalifa, Othman Omran
title An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
title_short An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
title_full An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
title_fullStr An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
title_full_unstemmed An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets
title_sort iot-platform-based deep learning system for human behavior recognition in smart city monitoring using the berkeley mhad datasets
publisher Multidisciplinary Digital Publishing Institute (MDPI)
publishDate 2022
url http://irep.iium.edu.my/100377/7/100377_An%20IoT-platform-based%20deep%20learning%20system.pdf
http://irep.iium.edu.my/100377/
https://www.mdpi.com/2079-8954/10/5/177/pdf?version=1664626799
_version_ 1746210127334080512
score 13.211869

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