Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Surasit Phokha
Kalasin University
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Experimental evaluation of an artificial intelligence system for automated mango classification Surasit Phokha; Wiriya Dangton; Viroch Sukontanakarn; Phisit Srinoi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i4.pp3919-3933

Abstract

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.
Fixed-vision based automated quality inspection and robotic nut sorting with Dobot Magician Phisit Srinoi; Surasit Phokha; Viroch Sukontanakarn; Thewin Sakunbunyong; Wiriya Dangton
Bulletin of Electrical Engineering and Informatics Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i4.11667

Abstract

This research presents a low-cost automated nut sorting system developed through laboratory testing to provide an affordable automation solution for small and medium enterprises (SMEs). The system integrates a fixed-vision camera with a Dobot Magician robotic arm, utilizing Python, OpenCV, and homography-based coordinate transformation for precise positioning. Performance was evaluated under three controlled lighting conditions with 25 samples each. Results indicate that lighting intensity significantly affects accuracy: low lighting (27.25 lux) yielded only 16% accuracy (mu=0.16, sigma approximately 0.3666), while high lighting (481.78 lux) suffered from overexposure and reflections. In contrast, optimal laboratory conditions (129.71 lux) achieved 100% classification accuracy (mu=1, sigma=0), demonstrating perfect consistency and stability. The study concludes that while the system offers a high-efficiency, budget-friendly alternative for SMEs, maintaining controlled, optimal illumination is critical for operational success. These findings provide a technical foundation for implementing cost-effective robotic sorting in real-world SME environments where high-cost sensor arrays are not feasible.
Co-Authors Phisit Srinoi Phisit Srinoi Thewin Sakunbunyong Viroch Sukontanakarn Viroch Sukontanakarn Wiriya Dangton