ECONOMIC EFFICIENCY OF IMPLEMENTING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN BEEKEEPING AND FORECAST INDICATORS FOR 2026–2030
DOI:
https://doi.org/10.5281/zenodo.21908254Abstract
The economic efficiency of implementing artificial intelligence (AI) technologies in the beekeeping
industry under the conditions of the digital economy, mechanisms for optimizing production processes, and
promising directions for the development of the industry are examined. The research is based on analytical
data concerning the application of smart sensors, Internet of Things (IoT) devices, machine learning, computer
vision, acoustic analysis, automated control systems, and digital logistics tools in beekeeping. Traditional and
AI-based production models are comparatively assessed in terms of labor costs, productivity, colony losses,
production costs, revenue, net profit, and profitability. The findings indicate that the implementation of AI
technologies can increase the average honey yield per hive to 22-25 kg, reduce labor costs by 25-35% and
production costs by 15-20%, and increase net profit by 30-50%. Using 100 bee colonies as an example, the
AI-based model demonstrates that total revenue may reach 120-125 million soums, total expenses 55-60
million soums, net profit 60-65 million soums, and profitability approximately 95-110%. Based on these baseline
indicators, a conditional scenario forecast for 2026-2030 has been developed.
Keywords
beekeeping, artificial intelligence, digital agriculture, smart hives, Internet of Things (IoT), machine learning, productivity, production costs, profitability, investment, forecasting, digital monitoring.References
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