Conveyor Belt Object Identification: Mathematical, Algorithmic, and Software Support

Nevliudov, I. Sh,; Yevsieiev, V. V.; Maksymova, S. S.; Omarov, A. O. M.; Klymenko, O. M.

Публікація:
Conveyor Belt Object Identification: Mathematical, Algorithmic, and Software Support

dc.contributor.author	Nevliudov, I. Sh,
dc.contributor.author	Yevsieiev, V. V.
dc.contributor.author	Maksymova, S. S.
dc.contributor.author	Omarov, A. O. M.
dc.contributor.author	Klymenko, O. M.
dc.date.accessioned	2023-11-15T09:42:20Z
dc.date.available	2023-11-15T09:42:20Z
dc.date.issued	2023
dc.description.abstract	This article is devoted to the development of a package identification system on a mixed conveyor sorting line with a vertical lift from Kapelou. In the conditions of modern Warehouse 4.0 systems requirements, a tasks number arise associated with automatic objects sorting in real time. One of the most common is QR codes using, as it is the most costeffective. But the introduction of automated systems for identifying objects on a conveyor line based on QR codes causes a number of tasks that are associated with the dynamic parameters of identifying the location of the package in the recognition zone, determining and localizing the location of the QR code, for further reading and decoding information about the package with further adoption decisions about its movement in the sorting system. The authors propose a solution to this problem by developing a module for identifying and recognizing objects on a conveyor line based on computer vision using a Raspberry Pi 4 Model B single-board computer with a developed method for processing a QR code image, the system structure, algorithmic and mathematical support have been developed. To check the correctness of proposed decisions, software was developed, and a number of natural experiments were carried out with different parameters (conveyor speeds, illumination, packaging feeding angles for the computer vision system) for the developed object identification system on the Kapelou sorting conveyor line, which showed a high processing speed and decoding data from a QR code.
dc.identifier.citation	Conveyor Belt Object Identification: Mathematical, Algorithmic, and Software Support / V. V. Yevsieiev, I. S. Nevliudov, S. S. Maksymova et all. // Applied Mathematics & Information Sciences : An International Journal. - 2023. - Vol. 17, No. 6. - P. 1073-1088.
dc.identifier.other	doi:10.18576/amis/170615
dc.identifier.uri	https://openarchive.nure.ua/handle/document/24755
dc.language.iso	en_US
dc.publisher	Natural Sciences Publishing (NSP)
dc.subject	Conveyor Belt
dc.subject	Object Indentification
dc.subject	Object Recognition
dc.subject	Raspberry Pi
dc.subject	QR-code
dc.title	Conveyor Belt Object Identification: Mathematical, Algorithmic, and Software Support
dc.type	Article
dspace.entity.type	Publication