ARTIFICIAL INTELLIGENCE-BASED INTELLIGENT SORTING OF FRUITS BY COLOR (Innovative technologies, 2026)
This paper presents the development of an automatic fruit sorting system based on color characteristics using an Arduino microcontroller and a TCS230 color sensor. The proposed system is designed to detect external color features of fruits in real time, process RGB color components, and classify fruits according to predefined criteria. The study focuses on automating quality assessment processes in agricultural and food production sectors.The system operation algorithm includes color data acquisition, object detection using infrared sensors, and control of a mechanical sorting mechanism. Sensor calibration was applied to reduce the influence of external lighting conditions and improve color detection accuracy. Experimental results demonstrated stable system performance and reliable color-based fruit classification.In addition, the paper discusses the potential integration of artificial intelligence techniques, particularly neural networks, to enhance sorting accuracy. Compared to conventional threshold-based methods, intelligent approaches allow more precise discrimination of subtle color differences. The obtained results indicate that the proposed system is a promising solution for improving efficiency and reliability in automatic fruit sorting applications.
Keywords: fruit sorting; color sensor; Arduino microcontroller; automated system; RGB color components; mechanical sorting; artificial intelligence; real-time processing