Роботи, що індексуються в Google Scholar
PERFORMANCE EVALUATION OF OBJECT DETECTION FOR TRAFFIC RULE VIOLATION MONITORING ON RASPBERRY PI WITH NPU
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
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Авторське право (c) 2026 Yevhen Fastiuk, Ruslan Bachynskyi

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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. 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. 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. 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. 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. 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. 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. Fastiuk, Y., & Huzynets, N. (2024). OPTIMIZATION OF THE ALGORITHM
- 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
- 8. Xing, Y., Han, X., Pan, X., An, D., Liu, W., & Bai, Y. (2024). EMG-YOLO:
- road crack detection algorithm for edge computing devices. Frontiers in Neurorobotics, 18. https://doi.org/10.3389/fnbot.2024.1423738
- 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
