International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

This paper presents the development and experimental validation of a method for automatic identification of apple varieties based on the analysis of visual features extracted from digital images. The proposed approach uses classical computer vision techniques without applying neural networks or deep learning, which makes the system interpretable, lightweight, and reproducible for laboratory and industrial use.
The algorithm includes the stages of image acquisition, preprocessing, object segmentation, feature extraction, and classification using statistical models such as Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), and logistic regression. The extracted features include geometric parameters (area, perimeter, circularity, eccentricity, axis ratio) and color characteristics (mean HSV values, red color percentage, hue distribution).
Experimental validation was performed on a dataset containing five apple varieties: Sinap Almaty, Fuji, Brebourne, Gold Delicious, and Hybrid. The system achieved an average classification accuracy of 90%, with the highest results for varieties with distinctive morphological or color characteristics. Comparative analysis with manual sorting demonstrated significant advantages in terms of processing speed, objectivity, and scalability.
The proposed method can be implemented on compact single-board computers, making it suitable for mobile quality control stations and automated sorting lines. Future work includes the integration of weight and texture parameters and the expansion of the variety database for broader applicability.

This article examines the use of computer vision and deep learning to automatically determine key quality indicators of apples, enhancing product quality. It describes a digital method for measuring apple size, ripeness, and variety classification using an automated optoelectronic system, achieving an accuracy of at least 86%. Advantages, limitations, and potential productivity benefits for Kazakhstan’s apple production are discussed. An algorithm developed with OpenCV in Python analyzes apple images to determine diameter, height, surface area, red color proportion, and external defects. Tested on “Sinap Almaty” apples, the method measures linear dimensions, crosssectional area, and redness percentage.

The essence of the concept “management of the strategy of innovation activity” is explored. The groups of factors of the external and internal environment that influence the management of the strategy of innovative activity of industrial enterprises are distinguished. The necessity of using methods and tools that will reduce or neutralize the factors of the external and internal environment and increase the effectiveness of the strategy of innovative activity of industrial enterprises is substantiated. The author’s definition of the theoretical essence of “management of the strategy of innovation activity” is proposed.

The improvement of the efficiency of agricultural machines of a modern technical level can be achieved when new methods of the theory of mechanisms and machines are used during calculations and design of their working bodies and in general of machine aggregates. The task of the research was to develop a new algorithm for solving the second problem of dynamics of lever mechanisms with electric drive, which are used in modern agricultural machines A new algorithm for solving the second problem of dynamics of lever mechanisms of agricultural machines equipped with an electric drive has been developed. The algorithm finds application in calculations of flat lever mechanisms of stationary agricultural machines.

This article shows the method and results of experimental RESEARCHES of machines for egg sorting into categories based on size and form using a vision system. The principal difference of the considered machine for automatic sorting of eggs into categories from existing sorting machines is the division of eggs into categories by size and the separation of substandard eggs in the flow. Experimental verification showed that the machine provides the division of eggs in size into four categories and the separation of eggs of irregular shapes and sizes in the flow. The accuracy of separation of eggs into categories depending on the performance. With a productivity of up to two eggs per second, the accuracy of egg separation averages 94.8%., With a productivity of three eggs per second was 87.4%.

High-speed crafts’ reliability as well as its passenger’s comfort and safety are closely related to the craft’s dynamics on sea waves. The resultant dynamics are governed by the quality of the motion control system and its capacity for quality kinematic data acquisition. Herein, we propose a novel method for determining accelerometers’ mounting positions within a hydrofoil ship. This method eliminates interference from the output of accelerometers and provides the capability of determining the amplification coefficients of the second derivative with respect to the height of the ship’s motion.

The article discusses the basic parameters that characterize a given project as an innovative design and technical solutions as an innovation.The requirements are analyzed for innovation in applied science projects and their ability to be efficient and competitive. Studied the conditions and opportunities for impact of these indicators on the economic result of many downstream enterprises. An attempt was made to determine the degree of innovation impact, which serves as a basis for assessing the design decisions. The following are findings with recommendations for the use of this method of evaluation.