Computer-aided design analysis of Honeybee colony using Images

Bee hive monitoring using AI has evolved in recent years as a result of advanced digital image processing. Honeybee Colony strength evaluation can aid apiary management and give significant research data in the face of the worldwide honey bee decrease. Manually quantifying bee cells, and categorizing them through visual evaluation and subjective judgement, is a labor-intensive task that is susceptible to errors and necessitates expertise of an inspector. This laborious task can be simplified with the aid of computer vision and Digital image processing. The focus of this study is to locate all cells accurately. The detected cells are further classified to know the swarm health and colony development. To ease the process, image segmentation was performed using deep convolutional neural network under various color models. The test was conducted on 50 images and their results are compared in terms of cell detection accuracy.