Smart City Gnosys

Smart city article details

Title	Deep Learning And Industrial Internet Of Things To Improve Smart City Safety
ID_Doc	17808
Authors	Asad U.; Mohammed A.S.
Year	2023
Published	2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023
DOI	http://dx.doi.org/10.1109/ICBATS57792.2023.10111164
Abstract	the Internet of Things (IoT) has grown rapidly in recent years, enabling the manufacture of a vast array of devices that may improve different operational components in a wide variety of enterprises. This study is being done to lay the groundwork for the establishment of "smart cities,"or metropolitan regions where robots will outnumber humans. Data sensitivity has increased, particularly in the commercial and industrial sectors of the economy. We will also go through the myriad security risks that have occurred because of this company's rapid growth. In this study, deep learning, perceptrons, and convolutional neural networks are highlighted as the deep learning (DL) approaches for IoT applications in smart cities. Deep learning, perceptrons, and convolutional neural networks are only a few of the additional methodologies considered. We also discuss the benefits and drawbacks of various types of safety precautions. Furthermore, we evaluate the lessons learned, the obstacles that remain, and the future trends in the use of DL approach to improve Industrial Internet of Things (IIoT) safety. © 2023 IEEE.
Author Keywords	Convolution Neural Network; Cyber Attack; deep learning; Industrial Internet of Things; Smart City

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