Project Grant 2549203
- This Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $300,000 in funding to Washington State University (WSU) from May 1, 2024 to April 30, 2026. The project aims to develop collaborative research using AI/ML methods to improve agricultural production and climate resilience in India. Key objectives include: Building and testing new AI-enabled infrastructure for in-field crop monitoring and phenotyping, with a focus...
- Kansas State University received a $399,992 Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) effective October 1, 2025, through September 30, 2028, to develop SMART SCOUT, an artificial intelligence (AI)-enabled computer vision system for real-time soybean crop monitoring and management. The system integrates advanced camera technology with AI algorithms to detect pest damage—particularly from soybean stem borers—identify...
- This EAGER (Early-concept Grants for Exploratory Research) federal Project Grant award of $300,000 is provided by the National Science Foundation through its Office of International Science and Engineering (OISE) program (CFDA 47.079). The goal of this 2-year project is to develop and deploy artificial intelligence (AI)-driven tools to enhance agricultural productivity and sustainability worldwide. The key products and services to be delivered include: (1) Developing hybrid machine learning...
- This $500,000 Project Grant award from the National Science Foundation (NSF) Office of International Science and Engineering (CFDA 47.079) supports the "LEVERAGING BIO-CHEMICAL AND GREENHOUSE GAS SENSORS FOR SUSTAINABLE AGRICULTURE INNOVATIONS (BIOSENSEINNOVATIONS)" project. The project aims to develop cutting-edge sensors that can detect nutrients, chemical compounds, soil microbiomes, and greenhouse gases in real-time to advance precision agriculture and promote sustainable farming...
- This $324,213 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a novel AI infrastructure to integrate multi-scale sensing data and 3D modeling for enhanced crop monitoring and assessment. The key products to be delivered include: An AI system that integrates satellite, drone, and in-situ sensor data to accurately model 3D crop structures, including both above- and below-ground...
- This $250,000 project grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund the development of a multi-modal integrated sensor system and through-the-soil wireless power transmission technique for continuous, real-time monitoring of soil variables over time and space. A collaboration between Tennessee Technological University, the University of Tennessee...
- The Department of Agriculture National Institute of Food and Agriculture awarded Purdue University $618,000 under the Agriculture and Food Research Initiative (AFRI) on April 1, 2026, to develop improved soybean cultivars through the Sustainable Soybean Symbiotic Synergy for Productivity (4S4P) project. The award funds research integrating traditional breeding with gene-editing technologies to enhance elite soybean varieties. The project builds on a discovery that blocking a shoot-to-root...
- The National Science Foundation awarded a $304,786 project grant to the Donald Danforth Plant Science Center under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a cyber-physical system for securely sharing agricultural data and lessons learned via edge computing. The three-year award beginning October 1, 2022 will support intersecting expertise in plant science, secure networked systems, software engineering, and geospatial science to mitigate challenges...
- This federal Project Grant award for $1,700,000 was provided by the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) to the University of Tennessee from July 1, 2024 to June 30, 2027. The award will support research to better understand the protein and amino acid composition of soybean seeds and the mechanisms underlying the "rebalancing" phenomenon, where soybean plants compensate for changes to their seed storage proteins. The project will collect...
- This $300,000 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a sustainable, intelligent wearable sensor system for continuous tree health monitoring. The primary goals are to: Create a biocompatible, ion-sensitive sensor array that can be implanted in a plant's xylem to continuously monitor water and nutrient uptake in real-time. Develop energy-harvesting techniques...
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.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $75.0k | 7/29/26 |