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All Journal CESS (Journal of Computer Engineering, System and Science) Informatik : Jurnal Ilmu Komputer Jurnal Teknologi Terapan DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Journal of Applied Engineering and Technological Science (JAETS) JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Madaniya
Abdur Rohman Harits Martawireja
Politeknik Manufaktur Bandung
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Developing Sorting Algorithm for SmartEdu Conveyor using Computer Vision Technology Ridwan; Yuliadi Erdani; Sarosa Castrena Abadi; Mochammad Dimas Anugrah; Abdur Rohman Harits Martawireja; Rizqi Aji Pratama
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): December 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.12434

Abstract

This study aims to develop a sorting algorithm for the SmartEdu Conveyor using computer vision technology to enhance accuracy and efficiency in automated sorting systems. The system integrates a Raspberry Pi 4 as the main processing unit and employs the YOLOv8 object detection algorithm to classify geometric objects moving on a conveyor belt. Images captured by an overhead camera are processed in real time, and the results are transmitted through the MQTT protocol using the Paho MQTT library. Node-RED functions as the Human-Machine Interface (HMI), while a Programmable Logic Controller (PLC) drives double-acting pneumatic cylinders to perform the sorting mechanism. Experimental tests conducted at three conveyor speeds demonstrate that the system achieves an average accuracy confidence of 89.38% at 1 cm/s, 78.57% at 1.7 cm/s, and 59.28% at 2.3 cm/s. Further performance evaluation using the Precision–Recall curve yields a mean Average Precision (mAP) of 0.993 at an Intersection over Union (IoU) threshold of 0.5, indicating highly accurate object detection capability. The proposed YOLOv8-based sorting system demonstrates reliable real-time operation, high precision, and robust communication between vision and control modules. It will be implemented as a SmartEdu teaching aid prototype to support automation learning and industrial training applications. This work contributes to educational automation by integrating an open-source vision algorithm with industrial control architecture.
Co-Authors Adhitya Sumardi Sunarya Agus Setiawan Setiawan Angga Putra Hafidzin Aris Budiyarto Atika Nur Rahmawati Dandi Cahyadi Dede Sujana Dede Sujana Ega Mardoyo Fitria Suryatini Gun Gun Maulana Hadi Supriyanto Hendy Rudiansyah Hendy Rudiansyah Hilman Mujahid Purnama Ismail Rokhim Moch Fikrie Dzulfikar Mochammad Dimas Anugrah Mohammad Harry Khomas Saputra Muhammad Taufik Nur Jamiludin Nur Wisma Nugraha Nuryanti Nuryanti Permata, Nia Nuryanti Pipit Novita Anggraeni Ridwan Ridwan Ridwan Rifa'i, Afaf Fadhil Rizqi Aji Pratama Sandy Bhawana Mulia Sarosa Castrena Abadi Setyawan Ajie Sukarno Siti Aminah Susetyo Bagas Bhaskoro Wahyu Adi Chandra Wahyudi Purnomo Yuliadi Erdani, Yuliadi