Researchers at the University of Exeter have made an exceptional breakthrough in combating the threat of unsettling Asian hornets by developing an artificial intelligence (AI) system. Named VespAI, this automated system boasts the capability to identify Asian hornets with exceptional accuracy, per the findings of the university’s recent study.
Dr. Thomas O'Shea-Wheller, from the Environment and Sustainability Institute from Exter's Penryn Campus in Cornwall, highlighted the system's user-friendly nature, emphasising its potential for widespread adoption, from governmental agencies to individual beekeepers. He described the aim as creating an affordable and adaptable solution to address the pressing issue of invasive species detection.
How VespAI Works
VespAI operates using a compact processor and remains inactive until its sensors detect an insect within the size range of an Asian hornet. Once triggered, the AI algorithm aanalyses aptured images to determine whether the insect is an Asian hornet (Vespa velutina) or a native European hornet (Vespa crabro). If an Asian hornet is identified, the system sends an image alert to the user for confirmation.
Record Numbers of Sightings
The development of VespAI is a response to a surge in Asian hornet sightings not only across the UK but also in mainland Europe. In 2023, record numbers of these invasive hornets were observed, posing a significant threat to honeybee populations and biodiversity. With just one hornet capable of consuming up to 50 bees per day, the urgency for effective surveillance and response strategies is paramount.
Addressing Misidentification
Dr. Peter Kennedy, the mastermind behind VespAI, emphasised the system's ability to mitigate misidentifications, which have been prevalent in previous reports. By providing accurate and automated surveillance, VespAI aims to improve the efficiency of response efforts while minimising environmental impact.
What The Testing Indicate?
The effectiveness of VespAI was demonstrated through testing in Jersey, an area prone to Asian hornet incursions due to its proximity to mainland Europe. The system's high accuracy ensures that no Asian hornets are overlooked, while also preventing misidentification of other species.
Interdisciplinary Collaboration
The development of VespAI involved collaboration between biologists and data scientists from various departments within the University of Exeter. This interdisciplinary approach enabled the integration of biological expertise with cutting-edge AI technology, resulting in a versatile and robust solution.
The breakthrough AI system, dubbed VespAI, as detailed in their recent paper titled “VespAI: a deep learning-based system for the detection of invasive hornets,” published in the journal Communications Biology. This publication highlights the notable discovery made by the researchers in confronting the growing danger of invasive species. As we see it, this innovative AI system offers hope for protecting ecosystems and biodiversity from the threats posed by Asian hornets.
