CARY — SAS wants to help save the world’s No.1 food crop pollinator — the honey bee. And it’s doing so right in the Triangle’s backyard.
To coincide with World Bee Day, the Cary-base software analytics firm today confirmed it is working on three separate projects where 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.
NON-INVASIVELY MONITORING BEEHIVE HEALTH
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 SAS Event Stream Processing and SAS Viya software.
By connecting sensors to SAS’ four Bee Downtown hives at its headquarters in Cary, NC, the team started streaming hive data directly 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. It’s 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 I’m 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.
VISUALIZING THE WORLD’S POLLINATOR POPULATIONS
SAS is also launching a data visualization that maps out bees “counted” around the globe for the World Bee Count, an initiative co-founded by the Center 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 planet’s 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 University’s 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 a visualization map to 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.
USING MACHINE LEARNING TO MAXIMIZE BEES’ ACCESS TO FOOD
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 mankind’s food supply.
In partnership with Beefutures, 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.
Original Article Source: WRAL TechWire