Experimental evaluation of an artificial intelligence system for automated mango classification

Surasit Phokha (Kalasin University)
Wiriya Dangton (Rajamangala University of Technology Isan)
Viroch Sukontanakarn (Rajamangala University of Technology Isan)
Phisit Srinoi (Rajamangala University of Technology Isan)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 15, No 4: August 2026

This study proposes the design and implementation of an intelligent mango sorting system capable of classifying mangoes into three categories: unripe, ripe, and rotten. The system integrates a programmable logic controller (PLC) to operate a conveyor mechanism, with user interaction facilitated through a human-machine interface (HMI) touchscreen panel. Image acquisition is performed using a universal serial bus (USB) webcam, while image processing and classification are handled by the CiRA CORE software utilizing artificial intelligence (AI) techniques. The classification results are transmitted to an Arduino microcontroller, which controls pneumatic actuators responsible for the physical sorting process. Experimental results demonstrate that the system can accurately classify mangoes with an overall success rate of 90%, indicating its potential for practical application in automated agricultural product sorting.