Cited by 39IoT and Edge/Fog ComputingVideo Surveillance and Tracking MethodsAdvanced Neural Network Applications

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

Open access
Ezzat, Mostafa Ahmed, Abd El Ghany, Mohamed A., Almotairi, Sultan, Salem, Mohammed A.-M.·2021·Sensors

Abstract

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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  • Some survey papers highlight the benefits of using specific datasets in VSSs.

    “Some survey papers highlight the benefits of using specific datasets in VSSs [8,9].”

    From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [8]

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Research works printed but not linked: 2

  1. [109]Zhao H. Yan Z. Wang H. Torresani L. Torralba A. SLAC: A sparsely labeled dataset for action classification and localization arXiv 2017 2 1712.09374
  2. [125]Avgerinakis K. Briassouli A. Kompatsiaris I. Smoke detection using temporal HOGHOF descriptors and energy colour statistics from video Proceedings of the International Workshop on Multi-Sensor Systems and Networks for Fire Detection and Management Antalya, Turkey 8–9 November 2012

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Authors
Ezzat, M. A., Abd El Ghany, M. A., Almotairi, S., & Salem, M. A.-M.
Affiliations
  • German University in Cairo (EG)
  • Electronics Department, German University in Cairo, Cairo 11511, Egypt
  • Majmaah University (SA)
  • Ain Shams University (EG)
Corresponding author
Almotairi, Sultan
Venue
Sensors
Publisher
MDPI AG
Published
2021-05-06
Volume
21
Issue
9
Pages
3222
ISSN
1424-8220 (ISSN-L)
OpenAlex
W3161800282
Cited by
39
References
151
Citations by year
2026: 8 · 2025: 9 · 2024: 5 · 2023: 8 · 2022: 8 · 2021: 1
FWCI
2.47
Type
journal article
Language
en
Open access
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Technischen Universität Darmstadt (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • TUbilio (Technical University of Darmstadt) (submittedVersion)
  • Technischen Universität Darmstadt (submittedVersion)
  • Technischen Universität Darmstadt (cc-by)
Funders
Majmaah University
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
Keywords
video surveillance, smart cities, edge computing, embedded systems, Internet of Things, big data analytics

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