Artificial intelligence in video surveillance systems for suspicious activity detection and incident response: A systematic review

Cabanillas-Carbonell, Michael; Sallari Rivera, Jhordan; Santivañez Muñoz, Jhoel

doi:10.12913/22998624/196795

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Tytuł artykułu

Artificial intelligence in video surveillance systems for suspicious activity detection and incident response: A systematic review

Autorzy

Cabanillas-Carbonell Michael , Sallari Rivera Jhordan , Santivañez Muñoz Jhoel

Treść / Zawartość

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Cabanillas-Carbonell_Rivera_Munoz_2025.pdf

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Identyfikatory

DOI

10.12913/22998624/196795

Warianty tytułu

Języki publikacji

Abstrakty

Artificial intelligence has proven to be a key tool to improve the efficiency of video surveillance systems, contributing to public safety. This systematic review aims to analyze the contributions of Artificial Intelligence in this field, in line with Sustainable Development Goal 16 (SDG 16), which promotes peaceful and inclusive societies. 145 articles extracted from major databases such as Scopus, WOS, ProQuest, EBSCO, IEEE Xplore, and ScienceDirect were analyzed. Using PRISMA methodology, inclusion and exclusion criteria were applied, resulting in 42 articles relevant to the review. The findings indicate that the use of advanced AI technologies, such as the Internet of Things, Computer Vision, and Edge Computing, are the most integrated with artificial intelligence, enhancing its capabilities in video surveillance systems. In this framework, Deep Learning stands out as an essential basis for optimizing these applications. Finally, the results of this review provide a solid foundation for future research on the use of Artificial Intelligence in video surveillance. The technologies evaluated have the potential to further contribute to the improvement of security and operational efficiency in different contexts and environments.

Słowa kluczowe

artificial intelligence AI video vigilance deep learning security SDG 16 Sustainable Development Goal 16

Wydawca

Lublin University of Technology
Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin

Czasopismo

Advances in Science and Technology. Research Journal

Rocznik

2025

Tom

Vol. 19, no. 3

Strony

389--405

Opis fizyczny

Bibliogr. 62 poz., fig., tab.

Twórcy

autor

Cabanillas-Carbonell Michael

mcabanillas@ieee.org

Facultad de Ingeniería, Universidad Privada del Norte, Lima, Perú

https://orcid.org/0000-0001-9675-0970

autor

Sallari Rivera Jhordan

N00295433@upn.pe

Facultad de Ingeniería, Universidad Privada del Norte, Lima, Perú

https://orcid.org/0009-0004-5917-9268

autor

Santivañez Muñoz Jhoel

N00254208@upn.pe

Facultad de Ingeniería, Universidad Privada del Norte, Lima, Perú

https://orcid.org/0009-0000-9987-3511

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).

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Bibliografia

Identyfikator YADDA

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