Automatic Conveyor Mechatronics System Using Raspberry Pi, HUSKYLENS, and Toggle-Switching Separators
Authors: Anthonnete Candelaria, Kyle Josiah Cañet, Carlo Ibañez, Jemima Dominique Miranda, Dave Franc Vergara, Yhuan Antonio Yacub
Advisers
Engr. Jean Lester M. Cachola
Discipline
Computer science & engineering
Abstract
This study developed an automatic conveyor mechatronics system intended to modernize mango sorting and quality-control processes. The system used a Raspberry Pi 5, a HUSKYLENS artificial-intelligence vision sensor, and toggle-switching separators to recognize, classify, and route products with limited human intervention. It also incorporated access control and renewable-energy features to support operational efficiency, reduce error, and improve productivity in agricultural and industrial settings. The study used experimental prototyping and a system-development methodology. The prototype was built around a Raspberry Pi 5 with Arduino Mega and Arduino Uno microcontrollers. A HUSKYLENS sensor performed real-time object classification, infrared sensors tracked products, servo motors directed products, and an RFID module restricted access to authorized users. A solar-powered automatic transfer switch supported continued operation. Hardware and software tests assessed functionality, and a descriptive survey using a five-point Likert scale was analyzed through weighted mean, frequency, and percentage. The developed system automated the detection, classification, and routing of mangoes. HUSKYLENS performed real-time recognition, the RFID module supported access security, and the conveyor and toggle-switching separators sorted products according to predefined criteria. Evaluation results were described as satisfactory in sustainability, portability, safety, economic viability, and compliance with engineering standards. Survey respondents also reported favorable perceptions of the system’s efficiency and reliability. The findings suggest that embedded systems, AI-based vision, and automated controls can support mango sorting and quality-control processes. The prototype was intended to reduce manual handling, limit errors, support workplace safety, and use solar energy. Its limitations included heavier-load handling and scalability. Further development and quantitative performance testing are needed before application in agricultural, warehousing, or logistics environments.
Keywords
huskylens, mechatronics, conveyor system, solar energy, raspberry pi, automated sorting
How to Cite
Use the format below when citing articles from this publication.
APA 7th Edition
Candelaria, A., Cañet, K. J., Ibañez, C., Miranda, J. D., Vergara, D. F., & Yacub, Y. A. (2026). Automatic Conveyor Mechatronics System Using Raspberry Pi, HUSKYLENS, and Toggle-Switching Separators. Ascendens Asia Singapore – Bestlink College of the Philippines Journal of Multidisciplinary Research Abstracts, 8(6), 11-11. Retrieved from https://ascendens.asia/AASgBCPJMRA/8/6/1705
Ascendens Asia Singapore – Bestlink College of the Philippines Journal of Multidisciplinary Research Abstracts (AASgBCPJMRA)
The Ascendens Asia Singapore–Bestlink College of the Philippines Journal of Multidisciplinary Research Abstracts (AASgBCPJMRA) compiles abstracts of research papers presented at Multidisciplinary Research Fests primarily organized by Ascendens Asia Singapore in partnership with Bestlink College of the Philippines.
Volumes
8 volumes
Issues
6 issues
ISSN
2661-4472
Publisher
Ascendens Asia Publishing Pte. Ltd.