TY - GEN
T1 - Integrating Computer Vision in a CODESYS PLC to Enable Intelligent Object Identification
AU - Filimonov, Daniil
AU - Onabek, Abdirakhman
AU - Smolyarchuk, Kir
AU - Alizadeh, Tohid
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This research investigates the synergy between com-puter vision and programmable logic controllers (PLCs) for enhancing material recycling efficiency. Focusing on aluminum can and glass bottle recycling, this study develops and simulates a user-centric vending machine system. The system employs a convolutional neural network (CNN) for accurate object recog-nition, integrated with a PLC-based control system via the OPC UA communication protocol. By incentivizing recycling through discount offers, the vending machine aims to promote sustainable waste management practices. Successful simulation demonstrates the feasibility of this approach, highlighting the potential for computer vision and PLC integration in the development of advanced recycling solutions.
AB - This research investigates the synergy between com-puter vision and programmable logic controllers (PLCs) for enhancing material recycling efficiency. Focusing on aluminum can and glass bottle recycling, this study develops and simulates a user-centric vending machine system. The system employs a convolutional neural network (CNN) for accurate object recog-nition, integrated with a PLC-based control system via the OPC UA communication protocol. By incentivizing recycling through discount offers, the vending machine aims to promote sustainable waste management practices. Successful simulation demonstrates the feasibility of this approach, highlighting the potential for computer vision and PLC integration in the development of advanced recycling solutions.
KW - Computer vision
KW - Convolutional neural network
KW - Industrial automation
KW - OPC UA
KW - Programmable logic controller
UR - http://www.scopus.com/inward/record.url?scp=85204293618&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85204293618&partnerID=8YFLogxK
U2 - 10.1109/ICOM61675.2024.10652332
DO - 10.1109/ICOM61675.2024.10652332
M3 - Conference contribution
AN - SCOPUS:85204293618
T3 - Proceedings of the 9th International Conference on Mechatronics Engineering, ICOM 2024
SP - 65
EP - 70
BT - Proceedings of the 9th International Conference on Mechatronics Engineering, ICOM 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Mechatronics Engineering, ICOM 2024
Y2 - 13 August 2024 through 14 August 2024
ER -