Review article
https://doi.org/10.32985/ijeces.16.6.4
Bibliometric Analysis of Scientific Production of Intelligent Video Surveillance
Wagner Vicente Ramos
orcid.org/0000-0001-6322-3525
; Universidad Nacional de Cañete Faculty of Engineering, School of Systems Engineering San Agustín Street No. 124, San Vicente de Cañete, Lima, Perú
*
Alex Pacheco Pumaleque
orcid.org/0000-0001-9721-0730
; Universidad Nacional de Cañete Faculty of Engineering, School of Systems Engineering San Agustin Street No. 124, San Vicente de Cañete, Lima, Perú
Jhonny Gavino Torres
; Universidad Nacional de Cañete Graduate School, Master's Degree in Higher Education and Research Av. Mariscal Benavides 1370 House of Culture, San Vicente de Cañete Lima, Peru
* Corresponding author.
Abstract
This article offers a bibliometric analysis of academic research in intelligent video surveillance, evaluating its evolution between 2000 and 2024. 1,343 documents were collected from the Scopus database and the PRISMA methodology was applied to organize the search and selection of relevant publications. The findings show a notable increase in the number of studies, reaching its highest point in 2022, driven by advances in artificial intelligence, the Internet of Things (IoT) and deep learning. China leads scientific production in this field, followed by India and the United States. Main research areas include real-time surveillance using deep learning methods, sequential and transfer learning techniques, as well as the use of advanced YOLO, Faster-RCNN and RFCN algorithms in controlled environments; however, detecting unusual behavior is a latent challenge.
Keywords
video; iot; cybersecurity; surveillance; behavioral detection;
Hrčak ID:
332898
URI
Publication date:
11.6.2025.
Visits: 288 *