Development of ai based larvae transfer machine for royal jelly production

dc.authorid0000-0001-6927-5123en_US
dc.contributor.authorGüneş, Hüseyin
dc.date.accessioned2024-05-21T13:09:12Z
dc.date.available2024-05-21T13:09:12Z
dc.date.issued2023en_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractHoneybees produce many different products beneficial to humans. One of these of is royal jelly which is the bee product with highest nutritional value but is most difficult to produce. The most time-consuming procedure in royal jelly production involves removing larvae with ideal size from the honeycomb cells and transferring them to queen cups. In order to increase the speed of the larva transfer process and perform it without labor power, a machine autonomically performing larva transfer was developed in three stages. Firstly, a CNC platform that can move on three axes above the honeycomb was created. In the second stage, a camera device was developed to image the larvae and mounted on the platform. Later larvae were photographed with this device and labelled. Tagged photos have been quadrupled by data augmentation methods. A Mobiledet+SSDLite deep learning model was trained with these photographs and this model identified larvae with ideal size with 96% success. Additionally, the central points of the honeycomb cells were identified with the Hough circles method. In the third and final stage, a device which can transfer the identified larvae from the honeycomb cells to the queen cups was developed and mounted on the platform. Later general software controlling the platform and devices was developed. At the end of this study, for the first time in the literature, an artificial intelligence-supported machine was developed for automatic transfer of ideal larvae from natural honeycombs for royal jelly production.en_US
dc.description.sponsorshipScientific Research Project Fund of Balikesir Universitesi 2017/193en_US
dc.identifier.doi10.15832/ankutbd.870464
dc.identifier.endpage220en_US
dc.identifier.issn1300-7580
dc.identifier.issn2148-9297
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85147828655
dc.identifier.scopusqualityQ3
dc.identifier.startpage209en_US
dc.identifier.trdizinid1224945
dc.identifier.urihttps://doi.org/10.15832/ankutbd.870464
dc.identifier.urihttps://hdl.handle.net/20.500.12462/14669
dc.identifier.volume29en_US
dc.identifier.wosWOS:000977218600019
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherAnkara Universityen_US
dc.relation.ispartofTarım Bilimleri Dergisien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBee Larvae Transferen_US
dc.subjectImage Processingen_US
dc.subjectMobiledet SSD Liteen_US
dc.subjectRoyal Jellyen_US
dc.titleDevelopment of ai based larvae transfer machine for royal jelly productionen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket

Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
hüseyin-güneş.pdf
Boyut:
2.04 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full text

Lisans paketi

Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama: