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BeeHero Launches X-Project to Help Track & Mitigate Giant Hornet Invasion

Early detection by remote sensors aims to help prevent agroeconomic disaster


Palo Alto, CA, USA – WEBWIRE
Predatory hornet in action
Predatory hornet in action

“Using our AI platform to identify a unique sensory signature of the AGH along with BeeHero’s leading-edge beehive monitoring technology will enable a ‘sentinel’ network of monitored hives spread across the US, thus offering an effective and fully automated early warning system for this new invasive pest,” said Dr. Evans. “If you can monitor it, you can manage it.”

If the spread of the predatory Asian Giant Hornet (AGH) in America is similar to the spread of the smaller Asian hornet in Europe, then the US could be facing the largest threat to bees ever. An invasion would also represent a major threat to US farming; honeybee pollination contributes an estimated $20 billion to US farm income. BeeHero, the Precision Pollination Services company, is launching an initiative out of its innovation wing, BeeHeroX, using its remote sensors to help track the spread of the invaders, helping beekeepers and food growers develop preemptive measures and mitigation tactics.

BeeHero applies remote sensor technology and data analytics to aid the management of honey bee health and pollination performance. Data generated from connected hive sensors and environmental parameters are analyzed by BeeHero’s machine-learning algorithms to provide key measures of hive health, strength, and pollination effectiveness. BeeHero can apply this expertise and its technology platform to remotely detect the presence of an AGH scouting at a beehive and then send an automatic alert to the beekeeper and relevant state officials.

Early detection of AGH scouts in an apiary before a mass attack on a beehive is critical for protecting the colony from total destruction as well as informing nest location surveys. Following the first confirmed US sightings of AGH in Washington State in December 2019, the USDA issued a New Pest Response Guideline that includes recommendations for identifying hornets, particularly using citizen scientists to report potential sightings. BeeHeroX will donate sensors to create an incursion network of beehives. Sensors will be located on hives at key strategic locations, such as areas surrounding previous sightings and also around ports and airports where the hornets may enter the country.

Hope in Early Detection
The lead scientist at BeeHeroX, Dr. Huw Evans, has already successfully identified unique acoustic signatures for both the native European Hornet and invasive Asian Hornet in Europe. A network of monitored hives proved an effective early warning system when field-tested and was deployed in areas under threat from Asian Hornet incursion. Once the AGH acoustic signature has been successfully profiled, BeeHero will set up a similar network in the US. 

“Using our AI platform to identify a unique sensory signature of the AGH along with BeeHero’s leading-edge beehive monitoring technology will enable a ‘sentinel’ network of monitored hives spread across the US, thus offering an effective and fully automated early warning system for this new invasive pest,” said Dr. Evans. “If you can monitor it, you can manage it.”

Honey bees in the US are already suffering from high mortality rates and weakening health; the annual average rate of colony loss reported by beekeepers over the last 10 years is 37%. Threats to honey bees include habitat loss, agrochemicals, pathogens, parasites, climate change, and the interactions between them. However, most beekeepers would agree that the biggest cause of colony losses has been at the hands of Varroa destructor, a non-indigenous parasitic mite imported from Asia about 30 years ago and has since colonized pretty much every beehive across the US. The arrival of AGH on US shores could push the beekeeping industry over the edge. 

For more information or to apply to participate, please email hello@beehero.io


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 Hornet
 Pollination
 Pollinator
 Agriculture
 Technology


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