How deep learning can save bees from colony collapse

Mar 24, 2018 at 10:00 am by Press Release


In Bee Movie, an animated feature from 2007, a friendship between a bee (voiced by Jerry Seinfeld) and a young woman (Renee Zellweger) leads to the world’s bee population reclaiming the honey it produces.

A decade later, a young woman who is real and with a self-described “penchant for cute, round things” — working with NVIDIA engineers and GPU-powered deep learning — may help to minimize the impact of a destructive parasite and lead to domesticated bees being returned to the almond-shape hive design that serves them so well in the wild.

Jade Greenberg, a 17-year-old junior at Pascack Hills High School in Bergen County, N.J., zeroed in on honey bees and the causes of colony collapse as the subject of a research project for her molecular genetics class.

Eventually, Greenberg focused on the threat posed by Varroa mites, a parasite thought to be one of the most frequent causes of collapses of domestic hives. Her research has led her to postulate that the long-accepted design of the Langstroth hive — the cabinet-like standard since its introduction in the 1850s — is a big reason Varroa mites have become such a big problem.

NVIDIA, GPUs and deep learning came into the picture when Jade’s father, a solutions engineer at Kinetica, teamed with Jacci Cenci, an NVIDIA solution architect, and they started applying their companies’ respective technologies to the problem. Linking sensors and cameras to a convolutional neural network, Cenci’s team began collecting data on hive conditions such as weight, humidity, temperature and population.

Ramping Up Detection

A variety of deep learning and machine learning technologies — including NVIDIA’s Jetson TX2 development kit, an NVIDIA DGX Station, TensorRT, a high-performance deep learning inference optimizer and the Microsoft Cognitive Toolkit deep learning framework — combine to rapidly detect and warn against the presence of Varroa mites.

The stack of NVIDIA hardware and software is able to optimize, validate and deploy trained neural networks for inferencing in the field, thereby alerting beekeepers of the potential for infestation sooner.

“If the weight decreases, the hive could be sick and bees are leaving. If the hive is heavy, it could mean lots of swarming, or high humidity might be present, which increases the odds of mite infestation,” said Cenci.

Armed with this extra information, which is converted into useful charts and graphs using Kinetica’s GPU-accelerated insight engine, Greenberg moved steadily from simply studying the problem to crafting a solution.

“We have better ways of collecting data, and we have better ways of observing bees in more detailed ways,” she said. “I’m surprised that this industry hasn’t moved past something designed in the 19thcentury. It’s time for a change.

Fighting Mites with Hive Design

Greenberg, who explains her work in a video below, has been using the data collected with the NVIDIA technology to guide her efforts to design a better hive. She’s learned that the different sizes and shapes of the entrances, the contrast with the natural almond shape of wild hives, and the fact that the queen is separated from the rest of the colony are potentially fatal flaws of the Langstroth hive design.

She also suggested that the larger spaces that bees occupy allow other mite-infected insects, such as moths, to enter the hive and become trapped, leading to further infestation.

In other words, AI is enabling Greenberg to pull back the curtain on the Langstroth hive’s failings, which may have been underestimated before now.

“It tells us in what ways the Langstroth hive is failing us when it comes to Varroa mite infestation,” she said.

It also is helping Greenberg refine her design, which, to be viable in the commercial beekeeping arena, must improve hive health while preserving the commercial capabilities of the Langstroth hive.

Greenberg and her bee hive design were recently awarded first alternate in the engineering category at the Nokia Bell Labs North Jersey Regional Science Fair. She’s also a finalist in the Intel International Science and Engineering Fair in May.

Her work and the technology backing her up will additionally be the subject of a session at the upcoming GPU Technology Conference in San Jose. Kinetica dashboards presenting the info will be rendered on an NVIDIA DGX Station AI supercomputer.






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