Application of Machine Learning and Deep Learning Models in the Supervision of Apiculture

Honey bees are well known for crop pollination and honey production which in turn plays a vital role in global agriculture. They face various threats from parasites, ants, hive beetles, pesticides, pollutants, toxins, and also hive robberies which could finally lead to the collapse of colonies. These major problems have led to the worldwide decline of honey bees. Thus, determining colony strength has gained importance in sustainable beekeeping. Machine Learning (ML) techniques provide various solutions for these problems by accurately monitoring and detecting the hive status. This paper reviews such techniques which help in monitoring and detection of other features. This helps the beekeepers to drive control over effective honey extraction and increase productivity.