Real-Time Beehive Monitoring and Control for Precision Beekeeping Using IoT

Climate change, pathogen-induced environmental impacts, pesticide use, habitat loss, and industrial agriculture are leading to a significant decline in biological diversity. These disruptions adversely affect ecological balance and have resulted in the decline of wild pollinators and honeybees, which play a vital role in natural ecosystems. Consequently, beekeeping has also come under threat, as honeybees are among the most important pollinator insects in nature. With advancements in technology, wireless sensor networks now widely used across various domains have also begun to be implemented for remote monitoring of beehives. Through these remote monitoring systems, the continuous observation of hive conditions has become possible.This study aims to develop a hive monitoring system that enables the real-time, remote observation of honeybee colonies via a wireless sensor network in order to prevent colony losses and enhance honey production. The proposed system consists of locally placed sensors positioned at different points within the hive to measure temperature, relative humidity, and comb weight, as well as a cloud server where all collected data are stored. In addition, the system incorporates software and a web-based platform capable of performing data analysis and enabling operations on the database for real-time monitoring of hive parameters. Users of the developed web system can access and analyze the collected data. Real-time monitoring of temperature and humidity inside the hive will provide beekeepers with valuable insights into the health and environmental conditions of their colonies. Ultimately, this system will support beekeepers, the apiculture industry, and the agricultural sector by contributing to emerging apicultural technologies and addressing the urgent need to mitigate honeybee colony collapse. The system was operated with an average data sampling interval of 2 seconds over a 48-hour test period, during which hive temperature was maintained within ±0.4 °C and humidity within ±3 % RH. These quantitative findings demonstrate the effectiveness of the proposed system in achieving stable real-time monitoring and control.