Electronic Bee-Veterinarian helps maintain healthy hives

Developed by a team at the University of California, Riverside (UCR), the  Electronic Bee-Veterinarian (EBV) uses low-cost heat sensors and forecasting models to predict when beehive temperatures may reach dangerous levels.

The system is said to provide remote beekeepers with early warnings, allowing them to take preventive action before their colonies collapse during extreme hot or cold weather or when the bees cannot regulate their hive temperature because of disease, pesticide exposure, food shortages, or other factors.  The work is detailed in ACM Transactions on Knowledge Discovery from Data.

In a statement, lead author Shamima Hossain, a PhD student in computer science at UCR, said: “We convert the temperature to a factor that we are calling the health factor, which gives an estimate of how strong the bees are on a scale from zero to one.”

This metric, with a score of ‘one' indicating the bees are at full strength, allows beekeepers unfamiliar with the underlying model to assess hive health quickly.

Honeybees pollinate over 80 crops and contribute an estimated $29bn annually to US agriculture, but bee populations have declined due to various factors including habitat loss, pesticide exposure, parasites, and climate change.

“Over the last year, the US lost over 55 per cent of its honeybee colonies,” said Boris Baer, a UCR professor of entomology. “We are experiencing a major collapse of bee populations, and that is extremely worrying because about one-third of what we eat depends on bees.”

Beekeepers rely on their own judgment and manual inspections to detect problems, which can lead to delayed interventions. With EBV, they can get real-time insights and predict conditions days in advance, significantly reducing labour costs, said Baer, who collaborated with Hossain and other scientists at UCR’s Bourns College of Engineering.

“People have dreamed of these sensors for a very long time,” said Baer. “What I like here is that this system is fully integrated into the hive setup that beekeepers already use.”

Temperature fluctuations are among the first responses to any kind of threat to a hive’s health. Honeybees maintain a precise internal hive temperature between 33° and 36°C, which is a requirement for proper brood development and colony survival, said Baer.

The EBV method is based on thermal diffusion equations and control theory, making its predictions interpretable to scientists and beekeepers, Hossain said. The model uses temperature data collected from low-cost sensors installed inside the hive, feeding that information into an algorithm that predicts hive conditions several days in advance.

In tests conducted at UCR’s apiary, the EBV method analysed data from 10 hives during initial development and later expanded to 25 hives. According to UCR, the technology has proven its effectiveness, detecting conditions that required beekeeper intervention.

The research team is working on the next phase, which is to develop automated hive climate controls that can be installed on hives and respond to EBV’s predictions, adjusting hive temperatures automatically.