Abstract
This article discusses integrating machine learning and IoT technologies into bee apiary management systems. The research aims to optimize bee conditions, improve their health and increase honey production. Using machine learning, large amounts of data collected by hive sensors are analyzed to predict and prevent various bee health problems effectively. Particular attention is paid to methods of controlling temperature in hives through pulse-width modulation technology, which provides accurate and energy-efficient regulation of temperature conditions. A method for predicting temperature in hives for effective apiary management is also proposed.
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