Project Grant 2520346
- This federal Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $175,000.00 to the University of Tennessee to develop an AI-powered agricultural response system called HARVEST. The project investigates smart farming technologies that use artificial intelligence (AI) to help farmers protect crops, use resources more efficiently, and reduce reliance on chemicals. Key innovations include an early-warning module to detect...
- 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 Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $399,992 to Kansas State University to develop an AI-enabled computer vision system called "Smart Scout" to help soybean farmers monitor crop health and estimate yields. The project aims to address the challenge of soybean lodging, where plants fall over before harvest, reducing yields and making harvesting more difficult. Smart Scout will integrate...
- 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 Project Grant award from the National Science Foundation's Office of International Science and Engineering (OISE) program (CFDA 47.079) provides $400,000 to Iowa State University to develop AI-based decision support tools for farmers to quickly identify and manage agricultural pests, diseases, and weeds. The project will create smartphone apps and a chatbot that allow farmers to take photos of problems and receive instant identification and management advice, making advanced pest control...
- This Project Grant award of $195,013 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will establish the AI4AG living lab at Cornell University. AI4AG will serve as an accessible testbed to accelerate the development and deployment of artificial intelligence (AI) technologies for agriculture. The project will create a shared space equipped with tools, data, and expertise to support AI research and testing in real-world agricultural...
- 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...
- This Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) is providing $300,000 to Georgia Tech Research Corporation to advance innovations in digital agriculture and optimization through an international research network. The "AI4OPT-AG" project will leverage controlled-environment agriculture and emerging technologies like artificial intelligence, robotics, and advanced data analytics to enhance global food...
- The National Science Foundation's Office of International Science and Engineering (OISE) awarded a $400,000 Project Grant titled "AI-ENGAGE: DEVA: Disease Detection and Effective Control Using Versatile UAVs and UGVs in Apple Orchards" to Purdue University. The project aims to develop an integrated robotic system that combines drones (UAVs) and ground robots (UGVs) with smart sensors and artificial intelligence (AI) to detect and precisely treat diseases like apple scab, fire blight,...
- This $590,706 Project Grant awarded by the U.S. Department of Agriculture's (USDA) Agriculture and Food Research Initiative (AFRI) program, supports a 3-year initiative by the American Farmland Trust (AFT) to leverage university-based research at the intersection of data science/AI and agricultural areas. The key objectives are to: (1) track and model changes in irrigation land cover patterns using AI-based big data applications, (2) better inform the future of irrigated row crops through...
This Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $225,000 to the University of Missouri System to develop an AI-driven "HARVEST" system that assists farmers in addressing agricultural challenges such as pest outbreaks, crop diseases, nutrient deficiencies, and water stress. The project leverages sensors, drones, and mobile robots to enable early detection and provide real-time guidance to farmers on optimizing the use of resources like water, fertilizers, and pesticides. This international collaboration across the U.S., India, Japan, and Australia aims to accelerate global food security and foster workforce development through student training in AI and digital agriculture. The HARVEST system integrates three core innovations: an early-warning module for rapid pest and disease detection, a digital twin platform for simulating farm management strategies, and a multimodal generative AI framework that adapts insights across diverse regions while preserving data privacy. The award commences on October 1, 2025, with a targeted completion date of February 29, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $225.0k | 8/4/25 |