Project Grant 2520136
- 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...
- 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 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $548,193 to Purdue University to develop an integrated network of small, plant-wearable sensors for early detection of pest infestations in agriculture. The sensor system uses advanced nanomaterials to identify volatile organic compounds released by plants as a distress signal when attacked by insects. This technology will enable real-time monitoring and early warning of pest damage...
- 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 $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...
- The National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program awarded a $1,000,000.00 Project Grant to the University of Missouri System, doing business as Missouri University of Science & Technology (Missouri S&T), to develop an automated pest management system for rural farms. The project aims to integrate artificial intelligence (AI), Internet of Things (IoT), machine learning, and affordable communication networks to reduce reliance on manual labor...
- 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 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 $649,999 Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports Farmsense, Inc., a self-certified small disadvantaged business, in developing novel sensor technologies for precise insect pest monitoring and surveillance in agricultural settings. The project aims to create a system inspired by how bats detect and discriminate between different insects, allowing for tracking of insect pests down to the...
- This $3,531,686 Project Grant, awarded by the U.S. Department of Agriculture's National Institute of Food and Agriculture under the Specialty Crop Research Initiative (CFDA 10.309) program, is intended to develop and transfer an automated and integrated mobile system (AIMS) for commercial harvest, in-field pre-sorting, and quality recording of harvested apples. The project aims to leverage recent progress in robotic harvesting and pre-sorting technologies to alleviate labor shortages and...
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, and powdery mildew in apple orchards. The goal is to help farmers reduce chemical use, labor costs, and improve crop productivity by identifying early signs of disease and applying targeted pesticide treatments. This 3-year project, running from October 2025 to September 2028, supports workforce development through educational and training activities in robotics and AI.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $400.0k | 8/4/25 |