CARY SAS wants to help save the worlds No.1 food crop pollinator the honey bee. And its doing so right in the Triangles backyard.

To coincide with World Bee Day, the Cary-base software analytics firm today confirmed it is working on three separate projectswhere technology is monitoring, tracking and improving pollinator populations around the globe.

They include observing real-time conditions of beehives using an acoustic streaming system; working with Appalachian State University on the World Bee Count to visualize world bee population data; and decoding bee communication to maximize their food access.

By applying advanced analytics and artificial intelligence to beehive health, we have a better shot as a society to secure this critically important part of our ecosystem and, ultimately, our food supply, said Oliver Schabenberger, COO and CTO of SAS, in a statement.

Researchers from the SAS IoT Division are developing a bioacoustic monitoring system to non-invasively track real-time conditions of beehives using digital signal processing tools and machine learning algorithms available in SASEvent Stream Processingand SAS Viya software.

By connecting sensors to SAS four Bee Downtown hives at its headquarters in Cary, NC, the team startedstreaming hive datadirectly to the cloud to continuously measure data points in and around the hive, including weight, temperature, humidity, flight activity and acoustics. In-stream machine learning models were used to listen to the hive sounds, which can indicate health, stress levels, swarming activities and the status of the queen bee.

To ensure only the hum of the hive was being used to determine bees health and happiness, researchers used robust principal component analysis (RPCA), a machine learning technique, to separate extraneous or irrelevant noises from the inventory of sounds collected by hive microphones.

The researchers found that with RPCA capabilities, they could detect worker bees piping at the same frequency range at which a virgin queen pipes after a swarm, likely to assess whether a queen was present. The researchers then designed an automated pipeline to detect either queen piping following a swarm or worker piping that occurs when the colony is queenless.

SAS said the acoustic analysis can alert beekeepers to queen disappearances immediately, which is vitally important to significantly reducing colony loss rates. Its estimated the annual loss rates of US beehives exceed 40 percent and between 25-40 percent of these losses are due to queen failure.

With this system, SAS said beekeepers will have a deeper understanding of their hives without having to conduct time-consuming and disruptive manual inspections.

As a beekeeper myself, I know the magnitude of bees impact on our ecosystem, and Im inspired to find innovative ways to raise healthier bees to benefit us all, said Anya McGuirk, Distinguished Research Statistician Developer in the IoT division at SAS.

The researchers said they plan to implement the acoustic streaming system very soon and are continuing to look for ways to broaden the usage of technology to help honey bees and ultimately humankind.

SAS is also launching a data visualization that maps out bees counted around the globe for theWorld Bee Count, an initiative co-founded by theCenter for Analytics Research and Education(CARE) at Appalachian State University.

The goal: to engage citizens across the world to take pictures of bees as a first step toward understanding the reasons for their alarming decline, SAS says.

The World Bee Count allows us to crowdsource bee data to both visualize our planets bee population and create one of the largest, most informative data sets about bees to date, said Joseph Cazier, Professor and Executive Director at Appalachian State Universitys CARE, in a statement.

In early May, the World Bee Count app was launched for users both beekeepers and the general public, aka citizen data scientists to add data points to the Global Pollinator Map. Within the app, beekeepers can enter the number of hives they have, and any user can submit pictures of pollinators from their camera roll or through the in-app camera. Through SAS Visual Analytics, SAS has created avisualization mapto display the images users submit via the app which, it says, could potentially provide insights about the conditions that lead to the healthiest bee populations.

In future stages of this project, SAS said, the robust data set created from the app could help groups like universities and research institutes better strategize ways to save these vital creatures.

Representing the Nordic region, a team from Amesto NextBridge won the 2020 SAS EMEA Hackathon, which challenged participants to improve sustainability using SAS Viya. Their winning project used machine learning to maximize bees access to food, which would in turn benefit mankinds food supply.

In partnership withBeefutures, the team developed a system capable of automatically detecting, decoding and mapping bee waggle dances using Beefutures observation hives and SAS Viya.

Observing all of these dances manually is virtually impossible, but by using video footage from inside the hives and training machine learning algorithms to decode the dance, we will be able to better understand where bees are finding food, said Kjetil Kalager, lead of the Amesto NextBridge and Beefutures team. We implemented this information, along with hive coordinates, sun angle, time of day and agriculture around the hives into an interactive map in SAS Viya and then beekeepers can easily decode this hive information and relocate to better suited environments if necessary.

SAS said this systematic real-time monitoring of waggle dances allows bees to act as sensors for their ecosystems. It may also uncover other information bees communicate through dance that could help us save and protect their population.

Excerpt from:
From streaming hive data to acoustics, SAS uses machine learning, analytics to boost bee populations - WRAL Tech Wire