Proceedings of International Scientific Conference „ALFATECH – Smart Cities and modern technologies“ (pp. 118-121)
АУТОР(И) / AUTHOR(S): Stefan ĆIRKOVIĆ 
, Nikola STANIĆ , Katarina KARIĆ
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DOI: 10.46793/ALFATECHproc25.118C
САЖЕТАК / ABSTRACT:
Monitoring and assessing air pollution levels in urban areas represents a key challenge in environmental protection and traffic management. This paper proposes a computationally implemented method for indirect air pollution assessment based on traffic density analysis, eliminating the need for direct sensor-based measurements of pollutant concentrations. The proposed system employs computer vision for real-time vehicle detection and classification, while air pollution levels are estimated using a mathematical model that accounts for the average emission rates per vehicle. The system architecture includes an embedded computer (Raspberry Pi) for video data processing, network infrastructure connectivity, and data transmission to a central server for further analysis and visualization. Experimental results confirm that the proposed approach enables reliable and efficient air pollution assessment under real-world conditions, opening avenues for enhancing environmental monitoring strategies and optimizing traffic flow in urban environments.
КЉУЧНЕ РЕЧИ / KEYWORDS:
Air pollution assessment, traffic analysis, IoT, computer vision, mathematical modeling, urban ecosystems
ПРОЈЕКАТ / ACKNOWLEDGEMENT:
This study was supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia, and these results are parts of the Grant No. 451-03136/2025-03/200132 with University of Kragujevac – Faculty of Technical Sciences Čačak.
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