Özet:

Abstract The purpose of this study is to anlalyze, identify and quantify the scope of research on real time surveillance video analytics (RTSVA), and to expose the study trends, development, and evolution in the SCOPUS database. An electronic search was used to find the most relevant articles. The studies for examination were obtained from the Scopus database. With the help of the R programming language and VOSviewer software, each composition was analyzed in various dimensions such as co-authorship, co-citation, conceptual structure, co-word occurrence, trend topics analysis, thematic map, and visualization analysis. Using strategic thematic maps we highlighted motor themes (edge computing, video analysis and deep learning), niche(autonomous vehicles, and block chain), basic(IoT, bandwidth and data handling) and emerging themes(mobile computing and learning models). RTSAV literature has evolved greatly over the previous decade, according to the research. Future researchers may refer to it. Using relation methods such as co-word, co-author, co-citation, bibliographic coupling and thematic map analysis revealed potential research areas in this study. The relational word cloud analysis shows that video analytics and deep learning are the two crux that connects to other frequently keywords in the study. A thorough review and meta-analysis would assist future scholars to develop a robust theoretical foundation. Scopus database was used for science mapping in this research. This study may assist new and existing researchers in identifying new research areas, appropriate sources and cooperation prospects, as well as making informed judgments. Findings related to evaluative and relational methods may aid novice researchers.

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