Computing Sciences Professor Awarded Grant from US Department of Agriculture
VILLANOVA, Pa. (July 16, 2024) 鈥� Venkata Siva Kumar Margapuri, PhD, assistant professor of Computing Sciences at 草榴社区 has been awarded a three-year, $749,086 grant by the (USDA) (NIFA) to utilize autonomous aerial vehicles (AAVs), computer vision and other artificial intelligence (AI) tools to study the abundance of Bombus species鈥攃ommonly known as bumblebees鈥攖heir relationship with wild flora and factors that affect pollinator health. Dr. Margapuri, a member of 草榴社区鈥檚 Center of Excellence in Enterprise Technology (CEET), will serve as the lead principal investigator on the project.
鈥淭his grant highlights the broad and innovative nature of computer vision and artificial intelligence application,鈥� said Dr. Margapuri. 鈥淚t also underscores the importance of utilizing creative, interdisciplinary research and tools to best address contemporary environmental issues that affect us all. We are grateful for this opportunity and for the USDA/NIFA鈥檚 recognition of the significant role computing scientists can play in studying our natural world.鈥�
Bombus are integral to biodiversity, but their global population is declining due to increased urbanization, among other factors. That decline can affect plant diversity, ecosystem stability, crop production, food security and human welfare. The project鈥檚 research team, which also includes two entomologists and a computing scientist from Kansas State University, aims to learn more about the pollinators and factors contributing to their population decline and health by studying the abundance and prevalence of Bombus and their food sources.
The researchers will fly AAVs over large swaths of agricultural land in Kansas, collecting detailed videos and images of the landscape to build a repository of visual data. That data will be uploaded to an AI-driven convolutional neural network (CNN) developed by Dr. Margapuri, which will have the ability to detect and classify both Bombus and plant species within the imagery. The neural network will initially be trained with more than 100,000 images of Bombus along with images of 150-200 flowering plant species, and its capabilities and accuracy will be enhanced in real time with the flow of new visual information from the AAVs. The detections, classifications and datasets provided by the CNN will be used to study the corollary nature of Bombus and floral abundance with extreme accuracy across these vast areas of land.
The team will also develop a free, public web application, on which researchers, land managers and environmental watchdogs will be able to upload their own visual data and utilize the neural network鈥檚 detection, classification, quantization and characterization tools to monitor pollinators and make informed decisions to ensure their health.
鈥淐ombining computer vision and AAVs gives us the unique opportunity to study these important pollinators and flora across expansive, diverse environments in a non-invasive manner that keeps fragile ecosystems intact,鈥� said Dr. Margapuri. 鈥淏y providing the public with access to our developed neural networks, stakeholders will have the ability to do the same, while also contributing to the system鈥檚 learning capabilities.鈥�
The grant was issued under the USDA/NIFA鈥檚 (AFRI) program Pollinator Health: Research and Application. The program supports projects that 鈥減romote healthy populations of animal pollinators in agricultural systems where reliance of crops on pollinators for pollination services is increasing and where declines of pollinators is evident.鈥�
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*This work is supported by the Pollinator Health: Research and Application no. 2024-67014-42301 from the U.S. Department of Agriculture's National Institute of Food and Agriculture.