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Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends

The automation strategy of today’s smart cities relies on large IoT (internet of Things) systems that collect big data analytics to gain insights. Although there have been recent reviews in this field, there is a remarkable gap that addresses four sides of the problem. Namely, the application of vid...

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Detalles Bibliográficos
Autores principales: Ezzat, Mostafa Ahmed, Abd El Ghany, Mohamed A., Almotairi, Sultan, Salem, Mohammed A.-M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124810/
https://www.ncbi.nlm.nih.gov/pubmed/34066509
http://dx.doi.org/10.3390/s21093222
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author Ezzat, Mostafa Ahmed
Abd El Ghany, Mohamed A.
Almotairi, Sultan
Salem, Mohammed A.-M.
author_facet Ezzat, Mostafa Ahmed
Abd El Ghany, Mohamed A.
Almotairi, Sultan
Salem, Mohammed A.-M.
author_sort Ezzat, Mostafa Ahmed
collection PubMed
description The automation strategy of today’s smart cities relies on large IoT (internet of Things) systems that collect big data analytics to gain insights. Although there have been recent reviews in this field, there is a remarkable gap that addresses four sides of the problem. Namely, the application of video surveillance in smart cities, algorithms, datasets, and embedded systems. In this paper, we discuss the latest datasets used, the algorithms used, and the recent advances in embedded systems to form edge vision computing are introduced. Moreover, future trends and challenges are addressed.
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spelling pubmed-81248102021-05-17 Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends Ezzat, Mostafa Ahmed Abd El Ghany, Mohamed A. Almotairi, Sultan Salem, Mohammed A.-M. Sensors (Basel) Article The automation strategy of today’s smart cities relies on large IoT (internet of Things) systems that collect big data analytics to gain insights. Although there have been recent reviews in this field, there is a remarkable gap that addresses four sides of the problem. Namely, the application of video surveillance in smart cities, algorithms, datasets, and embedded systems. In this paper, we discuss the latest datasets used, the algorithms used, and the recent advances in embedded systems to form edge vision computing are introduced. Moreover, future trends and challenges are addressed. MDPI 2021-05-06 /pmc/articles/PMC8124810/ /pubmed/34066509 http://dx.doi.org/10.3390/s21093222 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ezzat, Mostafa Ahmed
Abd El Ghany, Mohamed A.
Almotairi, Sultan
Salem, Mohammed A.-M.
Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title_full Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title_fullStr Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title_full_unstemmed Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title_short Horizontal Review on Video Surveillance for Smart Cities: Edge Devices, Applications, Datasets, and Future Trends
title_sort horizontal review on video surveillance for smart cities: edge devices, applications, datasets, and future trends
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124810/
https://www.ncbi.nlm.nih.gov/pubmed/34066509
http://dx.doi.org/10.3390/s21093222
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