Towards sustainable apiculture: GIS- and AI-assisted moni-toring of honey bees and floral resource networks

Abstract

Monitoring the foraging movements of free-living honey bees (Apis spp.), colony dynam-ics, and floral preferences at real-time and spatial scales holds great potential for sustain-able apiculture and the creation of floral corridors. This study explores a methodology in-tegrating sensor technologies, remote monitoring, big data and artificial intelligence (AI), as well as Geographic Information Systems (GIS) and remote sensing. Literature reports demonstrate significant advances in radar-based honey bee tracking systems, entrance sensors, floral resource mapping via re-mote sensing, and AI-supported image analysis. The proposed approach involves attaching lightweight transmitters to free-living honey bees to determine their spatial distribution, mortality events, and floral preferences. Data collected would be processed through GIS to generate large-scale floral maps, while AI-driven analyses would re-veal the behavioral relationships between bees and flora. This methodology aims to support sustainable apiculture in Turkey by identifying and strengthening floral corridors and optimizing migratory beekeeping practices.