13.02.2026; Рівне, Україна: V Міжнародна наукова конференція «Цифрове наукове суспільство: соціально-економічні, правові та міжнародні аспекти»
Роботи, що індексуються в Google Scholar

PERFORMANCE EVALUATION OF OBJECT DETECTION FOR TRAFFIC RULE VIOLATION MONITORING ON RASPBERRY PI WITH NPU

PDF

Опубліковано 15.02.2026

Як цитувати

Fastiuk, Y., & Bachynskyi, R. (2026). PERFORMANCE EVALUATION OF OBJECT DETECTION FOR TRAFFIC RULE VIOLATION MONITORING ON RASPBERRY PI WITH NPU. Матеріали конференцій МЦНД, (13.02.2026; Рівне, Україна), 137–141. https://doi.org/10.62731/mcnd-13.02.2026.004

Завантаження

Дані завантаження ще не доступні.
Google Scholar

Анотація

Traffic rule violations remain a primary cause of road accidents, yet the infrastructure used to detect them is often prohibitively expensive and complex. The reliance on high-performance and expensive sensors makes widespread deployment impractical, particularly in developing regions or rural areas where budget and power resources are limited.

Посилання

  1. 1. Jyothi, B., Pabbuleti, B., Sanjeev, G., Rao, K. V. G., Srilakshmi, S. S., Jee, A., Kumar, M. K., Bikku, T., & Reddy, C. R. (2025). Real-time vehicle detection and speed estimation system using Raspberry Pi and camera module. Bulletin of Electrical Engineering and Informatics, 14(6), 4962–4973. https://doi.org/10.11591/eei.v14i6.9931
  2. 2. Bharath, B., & Thirumalaiah, G. (2025). Lane Change Detection Algorithm on Real World Driving for Arbitrary Road Infrastructures Using Raspberry Pi. У INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION, COMMUNICATION, AND COMPUTING TECHNOLOGIES (с. 377–382). SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0013883200004919
  3. 3. Deshmukh, S., Atole, H., Rangwal, A., Kokil, B., & Saraswat, S. (2020). Traffic Rule Violation Detection System using Raspberry Pi and ML. International Journal of Science Technology & Engineering, 6(6), 7–12. http://www.ijste.org/articles/IJSTEV6I6002.pdf
  4. 4. Marpu, R. P., McNamara, K. J., & Gupta, P. (2025). The AI Shadow War: SaaS vs. Edge Computing Architectures (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2507.11545
  5. 5. Гузинець, Н. (2025). ВИКОРИСТАННЯ ОДНОПЛАТНИХ КОМП'ЮТЕРІВ ДЛЯ СИСТЕМ РОЗПІЗНАВАННЯ ОБ'ЄКТІВ. Grail of Science, (58), 779–784. https://doi.org/10.36074/grail-of-science.14.11.2025.091
  6. 6. Fastiuk, Y., Bachynskyy, R., & Huzynets, N. (2021). Methods of Vehicle Recognition and Detecting Traffic Rules Violations on Motion Picture Based on OpenCV Framework. Advances in Cyber-Physical Systems, 6(2), 105–111. https://doi.org/10.23939/acps2021.02.105
  7. 7. Fastiuk, Y., & Huzynets, N. (2024). OPTIMIZATION OF THE ALGORITHM
  8. FLOW GRAPH WIDTH IN NEURAL NETWORKS TO REDUCE THE USE OF PROCESSOR ELEMENTS ON SINGLE-BOARD COMPUTERS. Computer systems and network, 6(2), 228–238. https://doi.org/10.23939/csn2024.02.228
  9. 8. Xing, Y., Han, X., Pan, X., An, D., Liu, W., & Bai, Y. (2024). EMG-YOLO:
  10. road crack detection algorithm for edge computing devices. Frontiers in Neurorobotics, 18. https://doi.org/10.3389/fnbot.2024.1423738
  11. 9. Raspberry pi 5 with Hailo-8L Benchmark. (б. д.). Hailo Community. https://community.hailo.ai/t/raspberry-pi-5-with-hailo-8l-benchmark/746