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2024, Digitalne tehnologije i urbana bezbezdnost, pp. 171-183
Abandoned objects detection by integrating GIS and artificial intelligence in urban security
aUniversity of Belgrade, Faculty of Geography, Serbia + University of Kragujevac, Faculty of Science, Serbia
bUniversity of Belgrade, Faculty of Geography, Serbia

emailaleksandar.peulic@gef.bg.ac.rs, dejan@gef.bg.ac.rs, dusica.jovanovic@gef.bg.ac.rs, sanja.stojkovic@gef.bg.ac.rs
Keywords: security; GIS; abandoned objects; urban environment; YOLO
Abstract
This paper investigates the application of advanced computer vision, specifically the YOLO algorithm, in the domain of urban security using Edge Device and GIS technology. The focus is on the detection and identification of abandoned items such as suitcases, backpacks and bags, which are often important for assessing security risks in urban environments, including schools, as well as the potential detection of weapon use. Through data analysis and implementation of the YOLO model on an Edge Device, we investigate the real-time effectiveness of the system in detecting these objects in public places such as airports, train stations, squares, and school complexes. We also integrate GIS technology for geolocation and analysis of detected objects in the urban environment. The paper also analyses the practical implications of such a system for improving security and effective response to potential threats in urban areas. Through the study of this topic, the goal is to improve safety and prevention strategies in modern urban environments.

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article language: Serbian
document type: Conference Paper
DOI: 10.5937/UBUR24171P
published in Portal: 18/02/2025
Creative Commons License 4.0

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