This $250,037 Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research initiative led by the University of Memphis. The project aims to develop a networked cyber-physical system with advanced data analytics and integrated renewable energy storage to optimize crop production and energy efficiency in controlled-environment agriculture (CEA) facilities. Key objectives include: 1) integrating...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $451,000 in funding to Clemson University to develop a networked cyber-physical system (CPS) for controlled-environment agriculture (CEA). The key objectives are to reduce energy consumption and costs while optimizing crop production efficiency in CEA facilities. The project will integrate advanced data analytics, renewable energy, and energy...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) grant award (CFDA 47.070) provides $248,844 to Texas A&M AgriLife Research to develop a networked cyber-physical system (CPS) for controlled-environment agriculture (CEA). The project aims to optimize crop production and energy efficiency in CEA facilities to enhance food security and sustainability. Key products include: Integration of photosynthesis models with real-time biophysical...
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 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 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...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) will fund a $149,952 planning effort for the DFARM project. DFARM aims to pilot and evaluate a distributed system of smart, connected hydroponics to empower food-insecure households in Knoxville, Tennessee to produce their own food year-round, thereby increasing community food security. The planning grant will support an intensive community...
This $150,000 National Science Foundation project grant supports the development of smart tools and sensors to enhance ecosystem services and economic returns from regenerative farmland management practices. Awarded on March 15, 2021 under the Computer and Information Science and Engineering program (CFDA 47.070), the two-year grant funds Pecan Street Inc. to connect communities through sensors and data analytics to deliver improved environmental and economic outcomes. Cornell University and...
This $250,000 National Science Foundation project grant supports the development of spatiotemporally transferable machine learning algorithms for enabling cross-country and cross-hemisphere in-season crop mapping. Funded under the Computer and Information Science and Engineering program, principal investigator George Mason University will design algorithms trained with U.S. agricultural data that can be applied to satellite imagery of foreign countries to generate in-season crop maps without...
This federal Project Grant award, provided by the U.S. Department of Agriculture's National Institute of Food and Agriculture (CFDA 10.310 - Agriculture and Food Research Initiative), aims to develop a new decentralized wastewater-hydroponic system (WWHS) that leverages recent advances in sensor technology, wastewater treatment, hydroponics, and machine/reinforcement learning. The goal is to achieve stable and high vegetable production with minimized resource and energy consumption through the...