A Smart Beehive Energy Management System for Supporting Automatic Varroa Detection

This paper presents a model predictive control (MPC) algorithm for optimizing the energy operations of a smart beehive equipped with a photovoltaic panel, an electrical storage, and a vision system for automatic detection of Varroa-infested bees. A camera at the entrance of the beehive monitors the entering and exiting bees, and image processing algorithms are used to detect the presence of Varroa. The goal of the proposed energy management algorithm is to maximize the number of monitored bees (image acquisition and processing consume energy), while ensuring that the beehive does not run out of energy, so that monitoring can be ensured over a prolonged time. Simulation results on real data show that the proposed controller effectively manages the beehive, ensuring the achievement of the above objectives.