THEORETICAL FOUNDATIONS AND IMPLEMENTATION OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE AND COMPUTER VISION TECHNOLOGIES IN AUTOMATING METROPOLITAN ESCALATORS.

Authors

  • Pardaboyev Humoyun Basic Doctoral Student
  • Zaripov Bakhodir

Keywords:

artificial intelligence, computer vision, deep learning, YOLO, metropolitan, escalator,

Abstract

This study examines real-time monitoring and automatic management  of passenger flow on metropolitan escalators using artificial intelligence and computer  vision technologies. The aim is to develop the conceptual foundations of an automatic  hazard  detection  system  based  on  deep  learning  algorithms  (CNN,  YOLO,  transformer). Systematic literature analysis based on PRISMA principles, comparati ve  analysis,  and  conceptual  modeling  were  employed,  with  25  international  sources  analyzed.

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References

1. The number of passengers transported on the Tashkent metro increased by 20 million in 2025 // Gazeta.uz. — 2026.01.13. — URL: https://www.gazeta.uz/oz/2026/01/13/metro/

2. Passenger flow on the Tashkent metro increased by 57% in 2024 // Gazeta.uz. — 2025.01.27.

3. How does the Tashkent Metropolitan plan to solve the congestion problem? // Gazeta.uz. — 2024.10.14.

4. Sari M.I., Ibnugraha P.D. et al. Initial Estimation Method for Public Transport Passenger Density // IEEE Proc. — 2023. — DOI: 10.1109/GCAT59970.2023.10353287.

5. Distributed Deep Learning System for Real-Time Passenger Flow Measurement // Applied Intelligence (Springer). — 2025. — DOI: 10.1007/s10489-025-06954-9.

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Published

2026-09-20

How to Cite

THEORETICAL FOUNDATIONS AND IMPLEMENTATION OPPORTUNITIES OF ARTIFICIAL INTELLIGENCE AND COMPUTER VISION TECHNOLOGIES IN AUTOMATING METROPOLITAN ESCALATORS. (2026). INTERNATIONAL CONFERENCE ON INTERDISCIPLINARY SCIENCE, 3(8), 198-207. https://universalconference.us/index.php/icms/article/view/7777