Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It.

Simple Summary: Worldwide, honeybees (Apis mellifera L.) are involved in pollinating both wild and economically useful plants, while their products are also used by the food and pharmaceutical industries. But currently, apiculture is encountering the adverse effects of global climate change, including more variable rainfall, shifting seasonal precipitation, and increasing temperature averages. These changes threaten the sustainable future of apiculture as these anomalies have already contributed significantly to the economic downturn of the apiculture industry in recent years. In this review, we provide an overview of the current challenges faced by apiculture due to climate change, as well as artificial intelligence (AI) applications in apiculture that can assist to address them. AI has been utilized in various scientific aspects of apiculture, such as managing hives, maintaining health, detecting pests and diseases, monitoring habitats, and managing population distribution. This is achieved by analyzing data objects such as text, audio, images, videos, sensor readings, and numerical values to investigate, model, predict, and make supporting decisions. Several shortcomings of the existing AI application are identified in this review, and the knowledge gaps regarding the development of autonomous intelligent systems for sustainable beekeeping are also highlighted. Honeybees (Apis mellifera L.) are important for agriculture and ecosystems; however, they are threatened by the changing climate. In order to adapt and respond to emerging difficulties, beekeepers require the ability to continuously monitor their beehives. To carry out this, the utilization of advanced machine learning techniques proves to be an exceptional tool. This review provides a comprehensive analysis of the available research on the different applications of artificial intelligence (AI) in beekeeping that are relevant to climate change. Presented studies have shown that AI can be used in various scientific aspects of beekeeping and can work with several data types (e.g., sound, sensor readings, images) to investigate, model, predict, and help make decisions in apiaries. Research articles related to various aspects of apiculture, e.g., managing hives, maintaining their health, detecting pests and diseases, and climate and habitat management, were analyzed. It was found that several environmental, behavioral, and physical attributes needed to be monitored in real-time to be able to understand and fully predict the state of the hives. Finally, it could be concluded that even if there is not yet a full-scale monitoring method for apiculture, the already available approaches (even with their identified shortcomings) can help maintain sustainability in the changing apiculture. [ABSTRACT FROM AUTHOR]