DEVISING AN APPROACH TO CONDUCTING FULL-SCALE EXPERIMENTS IN PHYSICS THAT PROVIDES FOR THE IMPROVED EFFICIENCY WHEN MEASURING PHYSICAL QUANTITIES
Medetov B. Zhetpisbayeva A. Serikov T. Khamzina B. Akhmediyarova A. Yskak A. Zhexebay D. Albanbay N.
2025Technology Center
Eastern-European Journal of Enterprise Technologies
2025#3Issue 559 - 69 pp.
The object of this study is a procedure for measuring physical quantities under laboratory conditions at educational institutions. The issue related to this case is the lack of any comprehensive method and technical solution suitable for the experimental study of physics in both offline and online learning formats. To solve this problem, an approach has been proposed, based on computer vision technology and training special neural models to recognize objects in video frames that perform mechanical movement. The idea of the proposed approach is based on the hypothesis that by measuring the position of an object in video frames with sufficient accuracy, it is possible to determine the functional type of the law of its motion. Further, knowing the function of the law of motion, it is possible to calculate any physical quantities describing the process under consideration. The idea is implemented in the form of a technical solution, which is a set of prototypes of automated laboratory devices. The choice of the method for determining the law of motion was carried out using the analysis of the recognition error, measurement error, speed and resistance to external conditions of the Hough algorithmic method and the YOLOv8n neural network model. It is shown that the neural network method YOLOv8n has very high accuracy but low performance. The Hough method shows high performance but lower accuracy and resistance to external conditions. It was found that the accuracy of the YOLOv8n method is 4 times higher, but the execution speed is 10 times lower than that of the Hough method. However, in the case of artificial lighting and fixing the distance from the camera to objects, the Hough method provides 99.9% accuracy in recognizing an object in video frames. The obtained prototypes of devices can be used for further research to determine their impact on the quality of physics education Copyright
computer vision , Hough method , laboratory setups , online learning , video processing , YOLOv8n
Text of the article Перейти на текст статьи
Department of Radio Engineering, Electronics and Telecommunications, L. N. Gumilyov Eurasian National University, Satbaev str., 2, Astana, 010000, Kazakhstan
Department of Radio Engineering, Electronics and Telecommunications, S. Seifullin Kazakh Agrotechnical Research University, Zhenis str., 62, Astana, 010000, Kazakhstan
Department of Physics and Chemistry, S. Seifullin Kazakh Agrotechnical Research University, Zhenis str., 62, Astana, 010000, Kazakhstan
Department of Software Engineering, Satbayev University, Satbayev str., 22, Almaty, 050000, Kazakhstan
Software Development Department, Ghalam LLP, Turan ave., 89, Astana, 010000, Kazakhstan
Department of Electronics and Astrophysics, Al-Farabi Kazakh National University, Al-Farabi ave., 71, Almaty, 050040, Kazakhstan
Department of Cybersecurity, Information Processing and Storage, Satbayev University, Satbayev str., 22, Almaty, 050000, Kazakhstan
Department of Radio Engineering
Department of Radio Engineering
Department of Physics and Chemistry
Department of Software Engineering
Software Development Department
Department of Electronics and Astrophysics
Department of Cybersecurity
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026