Bostanbekov K., Nurseitov D. B., Sakypbekova M. Zh., Shekerbayeva Sh. N., Shayea I. Case studies of collecting and processing data on detecting people in urban transport // Bulletin of Abai KazNPU. Series of Physical and Mathematical Sciences. – 2025. – Vol. 91, No. 3. – DOI 10.51889/2959-5894.2025.91.3.017.

Abstract:

In the context of increasing urban mobility, the task of accurate passenger counting becomes critically
important for transportation infrastructure planning. The aim of this article is to develop a system for automatic
detection and counting of people in urban transport using modern computer vision methods. The paper
describes the stages of data collection and annotation, model training, and evaluation of its effectiveness. The
aim of this study is to develop a system for automatic detection and counting of people in urban transport using
modern computer vision methods. The paper describes the stages of data collection and annotation, model
training, and evaluation of its effectiveness. A specialized dataset was created (4,047 images, 8,918 objects),
and the model was trained to achieve an F1-score of 0.90. A series of experiments with different tracking
algorithms was conducted. The results confirmed the system’s high accuracy and real-time applicability. The
developed solution can be used for monitoring passenger flow, optimizing routes, and improving the efficiency
of urban transport management.

Link / DOI: https://doi.org/10.51889/2959-5894.2025.91.3.017