Collaborative Research: VINES: Track 1: NSF-MeitY: SoyWatch: Smart Sensing Network for Precision Soybean Breeding

This collaborative project will develop a smart farming system to monitor, assess, and support the selection of soybean growth and performance. Soybeans are important for food, animal feed, and cooking oil, but farmers in the United States and India face challenges from pests, diseases, and changing weather. The project will create a smart sensor network, NextG-enabled wireless communication, and advanced AI tools to monitor crops and soil conditions. The system will help soybean breeders understand crop status and make better decisions. This work brings together investigators from the University of Memphis, University of Missouri, Kennesaw State University, Indian Institute of Technology Delhi, S.K. University of Agricultural Sciences and Technology of Kashmir, and Indian Council of Agricultural Research National Soybean Research Institute to ensure the system works across farming environments. This collaborative project will advance next generation communication systems through integrated sensing and multimodal AI for agriculture. The research has three thrusts. The first thrust develops robust sensor arrays to measure soil nutrients, moisture, and environmental conditions. The second thrust designs energy efficient wireless communication systems using drone-supported data collection and passive sensing technologies to enable scalable field coverage. The third thrust develops multimodal large language models that synthesize sensor data, drone images, and environmental information to support crop phenotyping, pest management, and yield forecasting. The project will integrate these thrusts into a toolkit that combines sensing, wireless communication, and AI to support data driven agricultural insights. This collaborative project will advance interdisciplinary collaboration in smart agriculture, workforce development, international partnership between the United States and India, and economic outcomes for farming communities. The project will support cross-disciplinary training for students in agriculture, engineering, and AI, strengthening research and workforce development capacity in both countries. By facilitating the development of high yielding and pest resistant soybean varieties, this project will help farming communities, improve food security, and strengthen rural economies, while demonstrating how advanced sensor, wireless communication, and AI systems can jointly benefit society. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.