Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** native bees are a critical part…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** native bees are a critical part of our nation's ecological infrastructure. While much of media coverage is centered on support for honey bees, which are imported and domesticated, native bees are more effective pollinators than honey bees for many plants, while also being more vulnerable due to their reliance on dwindling native ecosystems. Despite native BEE's superior effectiveness, most agriculture practices rely on imported honey bees for pollination, often creating more pressure on native BEE populations. Part of the reason for this is a knowledge GAP in the existing pollinating services in a region; which native bees are in my area, which might support pollination of my crops, and how do i attract them to my fields? While some researchers attempt to fill this knowledge GAP through trapping, crowdsourcing, and direct observation, these methods have not provided sufficient data for most species and most regions. This leaves farmers that have sustainability goals incapable of targeting the right species for their region and crop(s) of choice.to this end, this project aims to develop a smart native BEE camera trap to provide this critical information in an accessible way, supporting both sustainable agriculture and conservation efforts. First, we will define the necessary quality of the imaging system for BEE species identification, then develop the imaging system itself. We will make a modular attachment to the trap, which will attract native bees to land on a specific spot by imitating a flower. When bees approach this attractant, the high resolution video will begin. This will result in a preliminary system fit for use by native BEE researchers and other entomologists. Development of the artificial intelligence methods for native BEE species identification, which will make the system accessible to a lay person, is intended for the phase II portion of this work.