Beewise has developed a hive system with image recognition to better monitor the health of bee colonies.
by SCOTT MARTIN
Honeybee colonies worldwide are under siege by parasites, but they now have a white knight: a band of Israeli entrepreneurs bearing AI.
Beewise, an Israel-based startup, is using AI in its small northern community on the border of Lebanon to monitor honeybee colonies. It’s secured seed funding of more than $3 million and launched its robo-hive sporting image recognition to support bee populations.
In the U.S., honeybee colonies have collapsed by 40 percent in the past year, according to a recent report. The culprit is widely viewed to be varroa mites, which feed off the liver-like organs of honeybees and larvae, causing weakness as well as greater susceptibility to diseases and viruses.
Farmers everywhere count on honeybees for pollination of fruits and vegetables, and many now have to rent colonies from beekeepers to support their crops. Without bees to pollinate them, plants would have a difficult time reproducing and bearing fruit for people to eat.
A cottage industry of small private companies and researchers alike is developing image recognition for early detection of the varroa mite so that beekeepers can act before it’s too late for colonies.
“We’re trying to work on the colony loss — I call it ‘eyes on the hives, 24/7,’” said Saar Safra, CEO and co-founder of Beewise.
Traditional Colony Work
Managing commercial hives is labor-intensive for beekeepers, who manually pull frames (see image below), or sections of the honeycombs, from beehives and visually inspect them.
This time-consuming work can span as many as 1,000 beehives under management by a single professional beekeeper. That means a beehive might not get inspected for several weeks as it waits in line for the busy beekeeper to come along.
A few weeks of an undetected varroa mite infestation can have disastrous results for bee colonies. Computer vision with AI provides a faster way to keep on top of problems.
By replacing that traditional manual process with image recognition and robotics, keepers can recognize and treat the problem in real time, said Safra.
Beewise has developed a proprietary robotics system that can remotely treat infestations.
“When you take AI and apply it to traditional industries, the level of social impact is so much bigger than when you keep it enclosed in high tech — NVIDIA GPUs are basically doing a lot of that work,” he said.
Robo Beehive AI
Beewise trained its neural networks on thousands of images of bees. Its convolutional neural networks are doing unsupervised learning capable of image classification to identify bees with mites in its autonomous hives now in deployment.
Once image classification has identified bees that have been infested with mites, a recurrent neural network makes a decision on the best course of action. That could include automatically administering pesticides by the robot or to quarantine the beehive frame from others.
Beewise has made this possible with its autonomous beehives that rely on multiple cameras. Images from these prototype hives are fed into the compact supercomputing of NVIDIA Jetson for real-time processing on its deep learning models.
“It’s a whole AI-based control system — our AI detects and identifies the varroa mite in real time and sterilizes it. Clean healthy colonies operate completely different than infested ones,” said Safra.