Apis Insight for Phenotype Classification and Hive Health Forecasting using IoT and Deep Learning

This research illuminates the pivotal quandary of bee health classification native to the Indian subcontinent, a crucial facet of maintaining agroecological equilibrium. Through a multifaceted integration of advanced computer vision, intricate deep learning paradigms, and hardware monitoring, the study explores the application of cutting-edge technologies to monitor and assess bee health and subspecies as well as beehive assessment. By incorporating hardware-based monitoring systems, the research exemplifies the vanguard potential of technologically entrenched methodologies in the realm of agricultural sustainability. This approach not only addresses the complexities of bee phenotype classification within the specified geographical context but also emphasizes the utilization of hardware components for real-time environmental data collection, fostering a paradigmatic shift in the axiomatic fulcrum of agro-symbiotic consilience.