Center for Digital Agriculture
Current Projects
REU Site: Drivers for Machine Learning and Artificial Intelligence Practices (MAPS)
Overview: Machine learning and artificial intelligence have demonstrated the potential to vastly alter the efficiencies with which we operate across many applications. Biological systems that stand to benefit from advanced techniques in machine learning and artificial intelligence include all areas of digital agriculture that impact the natural earth, plants, and animals. The Research Experience for Undergraduates (REU) Site projects represent research that addresses some of the most pressing challenges to the sustainability of our world, bringing together some of the most difficult challenges at the intersection of human behavior, natural systems, and cutting-edge technology. The project offers highly specialized workforce training to students with backgrounds in either computation or biological systems and offers training to work across disciplines. Equipping a generation of students to work across disciplines reveals the opportunity for addressing grand challenges with robust problem-solving.
Principal Investigator: Dr. Angela Green-Miller
Funding Period: May 30, 2023 – November 30, 2025
Funding Source: NSF
Funding Amount: $405,868
Collaborating Partnering Institutions: Tuskegee University
Robotics Integrated High Tunnels (RobInHighTs): Creating Profitable Food Oases in Urban Ecosystems
Overview: This project seeks to identify and promote Robot Integrated High Tunnels (RobInHighTs) as a major economic driver for successful urban, indoor, and emerging agricultural platforms. High tunnels are ephemeral structures that cover and protect crops, thereby extending the growing season by several months in midwestern climate zones. They have gained popularity over the last two decades in the urban and peri-urban setting due to their cost-effectiveness, adaptability, and low environmental costs. Though advantageous, high tunnels require extra management to ensure a quality crop and good production rates as the urban environment brings new challenges with unique pests and soil quality. The sustenance and economic viability of urban high tunnels are thus limited by the shortage and rising inequities in the urban agricultural workforce. The primary objective of the project is to demonstrate that the RobInHighTs platform can greatly automate routine high tunnel operations, leading to increased crop yield and reduced manual intervention while simultaneously preserving soil quality for sustained use.
Principal Investigator: Girish Krishnan
Funding Period: January 1, 2023 – December 31, 2025
Funding Source: USDA/NIFA
Funding Amount: $975,000
Collaborating Partnering Institutions: Tuskegee University
I-FARM: Illinois Farming and Regenerative Management Testbed
Overview: I-FARM (Illinois – Farming and Regenerative Management) testbed will accelerate creation, maturation, and adoption of new management technologies that are fundamentally more sustainable, profitable, affordable, and scale-neutral. I-FARM will provide comprehensive management practices for a farm-of-the-future and demonstrate their application on an 80 acre testbed. In the first three years, technologies matured will leverage existing strengths of our team, including improved precision farming with remote-sensing; new under-canopy autonomous robotic solutions for cover-crop planting, variable-rate input applications, and mechanical weeding; remote sensing technologies for animal health prediction; enabled by multimodal networking solutions for rural broadband connectivity and edge AI. The MyFarm app will provide farmers with an integrated dashboard that can be customized to the needs of their farm. Our focus on scale-neutral technologies can provide a solution to the worsening labor crisis for small farms and improve the sustainability of large and spatially heterogeneous farms. Technoeconomic simulations and farmer surveys will clarify barriers and incentives to adoption of sustainable technology to industry and farmers. Integrated extension activities will be conducted in a research space that is open to farmers, where farmers will be provided demonstrations and training, easing the adoption of new technologies and opening new markets for farmers. I-FARM team will engage with the Industry to help Industry create new data-driven products and services for farmers. An Industry Advisory Board and a Farmer Advisory Board will help optimize impact on farming practices. Together, these integrated suite of solutions will lead to sustainable ways of meeting growing demand for agricultural produce.
Principal Investigator: Dr. Girish Chowdhary
Funding Period: April 1, 2022 – March 31, 2025
Funding Source: USDA/NIFA
Funding Amount: $3,936,000.
Collaborating Partnering Institutions: Tuskegee University
Overview: CROPPS will develop new paradigms for observing, recording, and modulating plant responses to their environment via an Internet of Living Things (IoLT). CROPPS will integrate the latest advances in synthetic biology, nanotechnology, sensors, distributed computing, systems biology, and data analytics to create programmable plants that report their experiences in digital format and dynamically respond to signals derived from processed data. Simply put, CROPPS will develop the tools to listen and talk to plants and their associated organisms (i.e., microbiomes). Programmable plant systems will generate foundational discoveries through interactive experimental designs, and prototype translational solutions for improved crop performance in the field, with long-term impacts on sustainability, productivity, and profitability. CROPPS research will make tremendous strides toward Understanding the Rule of Life by Harnessing the Data Revolution, two of NSF’s Big Ideas, and will support activities that span NSF priority areas, including in Integrative Organismal Systems (IOS), Computer Information Science and Engineering (CISE), and Chemical, Bioengineering, Environmental, and Transport Systems (CBET).
Principal Investigator: Dr. Susan McCouch (Cornell PI) Dr. Stephen Moose (UIUC PI)
Funding Period: October 1, 2021 – September 30, 2026
Funding Source: NSF
Funding Amount: $25,000,000
Collaborating Partnering Institutions: Cornell University, University of Illinois, and University of Arizona.
Overview: The COALESCE project seeks to transform CPS capabilities in agriculture by developing a novel, context-aware cyber-agricultural system that encompasses sensing, modeling, and actuation to enable farmers to respond to crop stressors with lower cost, greater agility, and significantly lower environmental impact than current practices. The technical objectives are to embed biophysics in machine learning for individualized crop modeling, to apply multi-modal information fusion and robust learning for individualized sensing, to implement data-driven, multi-scale planning and reasoning, and to develop individualized sensing and actuation via autonomous robots with dexterous manipulators. Modeling of biophysical conditions in reasoning models contributes to CPS research areas in data analytics, information management, and real-time systems. The individualized sensing thrust contributes to data analytics, information management, and autonomy research areas. Multi-scale reasoning and farm management based on individualized actuation contributes to the areas of control, data analytics, autonomy, networking, safety, and real-time systems research areas.
Principal Investigator: Dr. Soumik Sarkar (Iowa State PI) Dr. Girish Chowdhary (UIUC PI)
Funding Period: March 15, 2021 – March 14, 2025
Funding Source: NSF
Funding Amount: $2,000,000
Collaborating Partnering Institutions: Iowa State University, University of Illinois, George Mason and University of Arizona.
Overview: The AIFARMS Institute will combine a broad and outstanding team of foundational AI researchers, world-leading AI-driven agricultural research, unique experimental testbeds, and an extensive education portfolio of unique digital agriculture degrees, workforce training and farmer outreach. Four tightly integrated, multidisciplinary thrusts will advance core AI research areas such as computer vision, machine learning, soft object manipulation and intuitive human-robot interaction to solve major agricultural problems: addressing labor shortages with autonomy, advancing efficiency and welfare in animal agriculture, enhancing environmental resilience of crops, and safeguarding soil health. World-leading researchers from our five academic and two industry partners will direct a team of PhD students and postdoctoral researchers, forming a research cohort trained to the highest level in both computer science and agriculture. Joint CS+Agriculture degree programs at BS and MS levels will help build a highly qualified workforce. Outreach efforts will work to ensure all communities benefit from emerging technologies. We will create the AIFARMS Hub, a global clearing house for AI-driven Agriculture research to foster and coordinate a large external community around AI-driven innovation in Agriculture, with a far broader research agenda than one Institute can tackle alone.
Principal Investigator: Dr. Vikram Adve
Funding Period: September 1, 2020 – August 31, 2025
Funding Source: USDA/NIFA
Funding Amount: $20,000,000
Collaborating Partnering Institutions: Michigan State University, Tuskegee University, University of Chicago, Donald Danforth Plant Science Center, Argonne National Lab, USDA-ARS.
NRI: INT: Increasing the Level of Autonomy for Agricultural Robots Through Effective Interaction and Programming Paradigms
Overview: Agriculture is currently facing a labor crisis. Automating large equipment only partially addresses this problem due to issues such as soil compaction, overuse of chemicals, and cost of equipment. Recent research has revealed that small, low-cost robots deployed beneath the crop canopy can coordinate to create more sustainable agroecosystems through techniques like mechanical weeding, spot spraying, and cover crop planting. These small robots may make it possible to for small and large farms to reduce costs of inputs in a scale-neutral fashion. However, before agbots can be ubiquitously used at scale for cost sensitive production systems like corn and soybean, they need to be made easy-to-use by growers who are managing large acreage with little time to spare. This proposal aims to develop software tools to make programming fleets of robots easier while providing tools for runtime monitoring. We will also develop the interaction modules for the agbots, through behavioral planning and interface design. Through intelligent interaction, we will enable natural collaboration with the robots on the field and effective remote supervision from afar. In this integrative research, our cross-disciplinary team combines experts from human-robot interaction, agricultural robotics, verification, programming languages, and experimental economics. Leveraging these strengths, and the UIUC Center for Digital Agriculture, we will develop a new autonomous farm testbed through this effort to advance the science and practice of coordinated agricultural robotics.
Principal Investigator: Dr. Katie Driggs-Campbell
Funding Period: September 1, 2020 – August 31, 2025
Funding Source: USDA/NIFA
Funding Amount: $1,200,000
Past Projects
Overview: Past advances in science and technology, coupled with effective translational research, have driven dramatic gains in the productivity of agricultural systems. Current and future challenges demand transformational breakthroughs, rapid adoption of innovations, and consumer acceptance of these solutions. Ultimately, the success of modern agriculture, and the realization of food security will depend on enhancing the scale, speed, and interactivity of communication throughout agricultural systems. We propose to design and implement Digital Infrastructure for Research and Extension on Crops and Technology for Agriculture (DIRECT4AG). The DIRECT4AG platform will demonstrate on-farm how sensors, novel genetics, and data analytics can provide rich datasets for monitoring water use and agricultural management strategies, which will better inform decision support tools for enhancing the efficiency of maize production. A systems-level approach that integrates data from the entire growing season and multi-scale data layers will identify new insights into complex interactions. The data and capabilities of DIRECT4AG will enable innovative approaches to delivering digital agriculture to both large-scale farms in the Midwest corn belt and to Limited-resource, Small-scale and Socially Disadvantaged Farmers within the Black Belt Counties in Alabama. Design of both the platform and the research has incorporated stakeholder feedback from its inception and engagement with producers is emphasized throughout the project. Overall, the DIRECT4AG platform will establish an efficient feedback loop that transforms the concept of cooperative Extension for the era of digital agriculture, enabling it to evolve and keep pace with the ever-changing advancements in research and technology.
Principal Investigator: Dr. Anthony (Tony) Studer
Funding Period: June 1, 2021 – May 31, 2024
Funding Source: USDA/NIFA
Funding Amount: $822,906
Collaborating Partnering Institutions: Tuskegee University
Overview: This project seeks to identify and promote Robot Integrated High Tunnels (RobInHighTs) as a major economic driver for successful urban, indoor, and emerging agricultural platforms. High tunnels are ephemeral structures that cover and protect crops, thereby extending the growing season by several months in midwestern climate zones. They have gained popularity over the last two decades in the urban and peri-urban setting due to their cost-effectiveness, adaptability, and low environmental costs. Though advantageous, high tunnels require extra management to ensure a quality crop and good production rates as the urban environment brings new challenges with unique pests and soil quality. The sustenance and economic viability of urban high tunnels are thus limited by the shortage and rising inequities in the urban agricultural workforce. The primary objective of the project is to demonstrate that the RobInHighTs platform can greatly automate routine high tunnel operations, leading to increased crop yield and reduced manual intervention while simultaneously preserving soil quality for sustained use.
Principal Investigator: Naveen Kumar Uppalapati
Funding Period: March 1, 2023 – February 28, 2024
Funding Source: iSEE
Funding Amount: $30,000
Using Data-Driven Approaches To Develop Effective Social Media Marketing Strategies For Small And Medium-Sized Farms
Overview: Direct-to-consumer (DTC) marketing is vital to the profitability and sustainability of small and medium-sized farms. However, owners of such farms tend not to be digital natives, and often lack relevant knowledge of and experience with digital marketing tools that can inexpensively complement conventional DTC marketing channels.
The overall goal of the proposed project is to help small and medium-sized farms increase their profitability, by strengthening existing farm-customer relationships and enhancing access to new markets through the effective use of social media. Specifically, a mixed-methods, holistic approach will be used to provide farmers with evidence-based, easy-to-follow guidelines on effective message-design techniques that will motivate consumer engagement and elicit positive attitudes. The objectives supporting this goal include (i) using computational approaches to learn how various existing designs of Facebook brand posts by small and medium-sized farms foster consumer engagement; (ii) conducting an experiment-embedded survey to examine the effects of Facebook ad design on consumers’ engagement behaviors and attitudes toward farm brands and products, as well as the mechanisms that underlie such effects; and (iii) developing best-practices guidelines for social media marketing, with a focus on Facebook, tailored directly to the needs of small and medium-sized farms.
Principal Investigator: Dr. Leona Yi-Fan Su
Funding Period: January 1, 2022- December 31, 2023
Funding Source: USDA/NIFA
Funding Amount: $299,969.00.
Center for Research on Autonomous Farming Technologies (CRAFT)
Overview: Agriculture is currently facing a labor crisis. Automating large equipment only partially addresses this problem due to issues such as soil compaction, overuse of chemicals, and cost of equipment. Recent research has revealed that small, low-cost robots deployed beneath the crop canopy can coordinate to create more sustainable agroecosystems through techniques like mechanical weeding, spot spraying, and cover crop planting. These small robots may make it possible to for small and large farms to reduce costs of inputs in a scale-neutral fashion. However, before agbots can be ubiquitously used at scale for cost sensitive production systems like corn and soybean, they need to be made easy-to-use by growers who are managing large acreage with little time to spare. This proposal aims to develop software tools to make programming fleets of robots easier while providing tools for runtime monitoring. We will also develop the interaction modules for the agbots, through behavioral planning and interface design. Through intelligent interaction, we will enable natural collaboration with the robots on the field and effective remote supervision from afar. In this integrative research, our cross-disciplinary team combines experts from human-robot interaction, agricultural robotics, verification, programming languages, and experimental economics. Leveraging these strengths, and the UIUC Center for Digital Agriculture, we will develop a new autonomous farm testbed through this effort to advance the science and practice of coordinated agricultural robotics.
Principal Investigator: Dr. Girish Chowdhary
Funding Period: October, 2020 – October 2022
Funding Source: DPI
Funding Amount: $125,000
Collaborating Partnering Institutions: University of Chicago