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

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

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Abstract

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.

Item Type:	Article (Journal)
Uncontrolled Keywords:	smart cities; Internet of Things; neural networks; video surveillance; deep learning; artificial intelligence; Berkeley MHAD Datasets
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Prof. Dr Othman O. Khalifa
Date Deposited:	03 Oct 2022 10:07
Last Modified:	03 Oct 2022 10:11
URI:	http://irep.iium.edu.my/id/eprint/100377

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