PRAĆENJE AKTIVNOSTI PČELA PRIMENOM RAČUNARSKE VIZIJE

Abstract

Computer vision as a tool enables automated processing of visual information and provides the possibility of significant improvement of the agricultural production process. This paper presents the results of the application of the YOLO algorithm for monitoring bees at the entrance to the hive. The applied model achieved a detection accuracy of 92.86% and was implemented on a Raspberry PI 4 computer system. This small computer system can be used for further field testing, where the activity of bees at the entrance to the hive is monitored via video recording.