OLIVE RIPENESS DETECTION SYSTEM

dc.contributor.authorBizhigit, Nurbol
dc.contributor.authorArslanov, Smagulkassym
dc.contributor.authorShadiyev, Akmal
dc.contributor.authorKhavazmatov, Sarvar
dc.contributor.authorDunenov, Alisher
dc.contributor.authorDunenov, Alisher
dc.date.accessioned2024-06-12T12:10:44Z
dc.date.available2024-06-12T12:10:44Z
dc.date.issued2024-04
dc.description.abstractAbstract—As acute labor shortages and brain drain are being monitored in Europe, the demand for experienced specialists and labor in various fields is increasing. One such field is agriculture, specifically the olive industry. As the olive industryis one of the historically and economically significant aspects of life in the Mediterranean part of Europe, the solution of farming automatization and data-driven farming would be vital. To address this issue, we are introducing - the “Olive Ripeness Detection System.”, an automated image-processing tool designed to estimate the ripeness of olives accurately. Our system is a prerequisite system for automated means of harvesting high quality olive fruits in organic farms, which provides data-driven decisions for the farmers.en_US
dc.identifier.citationBizhigit, N. Arslanov, S. Shadiyev, A. Khavazmatov, S. Dunenov, A. (2024). Olive Ripeness Detection System. Nazarbayev University School of Engineering and Digital Sciences.en_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7843
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectType of access: Restricteden_US
dc.titleOLIVE RIPENESS DETECTION SYSTEMen_US
dc.typeBachelor's thesisen_US
workflow.import.sourcescience

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