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DEVISING AN APPROACH TO CONDUCTING FULL-SCALE EXPERIMENTS IN PHYSICS THAT PROVIDES FOR THE IMPROVED EFFICIENCY WHEN MEASURING PHYSICAL QUANTITIES

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dc.contributor.author Medetov, B.
dc.contributor.author Zhetpisbayeva, A.
dc.contributor.author Serikov, T.
dc.contributor.author Khamzina, B.
dc.contributor.author Akhmediyarova, A.
dc.contributor.author Yskak, A.
dc.contributor.author Zhexebay, D.
dc.contributor.author Albanbay, N.
dc.date.accessioned 2025-12-25T07:54:24Z
dc.date.available 2025-12-25T07:54:24Z
dc.date.issued 2025
dc.identifier.citation Medetov, B., Zhetpisbayeva, A., Serikov, T., Khamzina, B., Akhmediyarova, A., Yskak, A., Zhexebay, D., Albanbay, N. (2025). Devising an approach to conducting full-scale experiments in physics that provides for the improved efficiency when measuring physical quantities. Eastern-European Journal of Enterprise Technologies, 3 (5 (135)), 59–69. https://doi.org/10.15587/1729-4061.2025.333084 ru
dc.identifier.issn 1729-3774
dc.identifier.other doi.org/10.15587/1729-4061.2025.333084
dc.identifier.uri http://repository.enu.kz/handle/enu/29081
dc.description.abstract 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 ru
dc.language.iso en ru
dc.publisher Eastern-European Journal of Enterprise Technologies ru
dc.relation.ispartofseries 3 (5 (135)), 59–69;
dc.subject video processing ru
dc.subject laboratory setups ru
dc.subject YOLOv8n ru
dc.subject Hough method ru
dc.subject computer vision ru
dc.subject online learning ru
dc.title DEVISING AN APPROACH TO CONDUCTING FULL-SCALE EXPERIMENTS IN PHYSICS THAT PROVIDES FOR THE IMPROVED EFFICIENCY WHEN MEASURING PHYSICAL QUANTITIES ru
dc.type Article ru


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