Resumen

BARRAGAN-HUAMAN, Hernán Yonathan; CATANO-ANAZCO, Kevin Elías; SEVINCHA-CHACABANA, Mauricio Adriano  y  VARGAS-SALAS, Obed. Artificial intelligence and video surveillance in space-time crime prediction and detection: a systematic review. Rev. Crim. [online]. 2023, vol.65, n.1, pp.11-25.  Epub 01-Jun-2023. ISSN 1794-3108.  https://doi.org/10.47741/17943108.398.

In today’s society, crimes are increasing, particularly in the city of Bogota, which has caused many inconveniences to the National Police of Colombia, as well as to the citizen security centers. Given this situation, a time-space prediction of crime and crime hotspots has been proposed with the help of artificial intelligence. Therefore, this paper aims to analyze, summarize, interpret and evaluate the various techniques of space-time prediction of crime with an intelligent view. Due to the very nature of the research, a descriptive-qualitative approach methodology was used, with which structured observation sheets were designed to systematize information from five databases: Scopus, Web of Science, IEEE, ACM, Springer; these publications span from 2019 to June 2021. Consequently, a total of 3015 studies were found, after the screening process and verification of exclusion and inclusion criteria, 132 articles were selected, then questions were applied Psychologist Internal Resident (PIR), thus leaving 18 articles. The main findings indicate that neural network algorithms proved to be one of the most effective methods for the detection of crime hotspots, given that the great advances in technology would help in the coming years to quickly and effectively predict criminal acts and crimes located in any region of the Latin American continent.

Palabras clave : Criminology; artificial intelligence; crime detection; social geography; Geographic Information Systems (GIS); crime maps; spatio-temporal analysis.

        · resumen en Español | Portugués     · texto en Español     · Español ( pdf )