Development of AI Based Larvae Transfer Machine for Royal Jelly Production

Abstract

Honeybees 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.

Keywords

• bee larvae transfer
• image processing
• mobiledet ssd lite
• royal jelly

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