National Science Foundation Grant Number 2020-67021-32975
Addressing the grand challenge of ensuring sustainable agricultural production and communities necessitates advancements in plant and crop science, weather and climate forecasting, hydrologic modeling, and water management, particularly within the integrated ecosystem of climate-food-water. However, recent advances in digital agriculture and AI have largely occurred in isolation, failing to tackle interconnected ecosystem challenges due to data issues, modeling assumptions, and usability concerns. This planning grant project aims to address these challenges through five fundamental areas of AI research: representation, science-guided learning, reasoning/planning, explainability/trust, and robustness. By collaborating with domain science researchers, AI experts, sustainability organizations, growers, and producers, the project aims to define viable AI approaches and research directions for achieving a sustainable integrated climate-food-water ecosystem.
David Ebert, PhD (PI)
Melba Crawford, PhD (Co-PI, Purdue University)
Hank Jenkins-Smith (Co-PI)
Marcie King
David Ebert, PhD
Gopichandh Danala, PhD
Wolfgang Jentner, PhD
Catherine Donner, MS/GRA
Travis E Lloyd, BS/FYRE
Jennifer Koch, Phd
Wolfgang Jentner, PhD
Mehreen Habib, MS/GRA
Richa Bhattarai, PhD & MS/GRA
David Ebert, PhD
Hank Jenkins-Smith, PhD
Wolfgang Jentner, PhD
Charles Nicholson, PhD
Matthew Beattie, PhD
Wolfgang Jentner, PhD
Gopichandh Danala, PhD
Catherine Donner, MS/GRA
Richa Bhatterai, MS/GRA
David Ebert, PhD
Hank Jenkins-Smith, PhD
Jennifer Koch, PhD
Gopichandh Danala, PhD
Wolfgang Jentner, PhD
Catherine Donner, MS/GRA
Mehreen Habib, MS/GRA
Richa Bhattarai, MS/GRA
This collaborative research initiative is a joint effort between the Data Institute for Societal Challenges (DISC) and the United States Department of Agriculture – Agricultural Research Services (USDA-ARS). The primary focus of this work is to conduct data science-enabled research aimed at enhancing sustainable agricultural practices through the study of ecosystem dynamics in the vast tallgrass prairie of the US southern Great Plains. This interdisciplinary research work spans from developing predictive modeling techniques for vegetation to comprehending various aspects of ecosystem functioning. Researchers explore topics such as vegetation phenology and changes in ecosystem fluxes, including Evapotranspiration (ET), Ecosystem Respiration (ER), Gross Primary Productivity (GPP), and Net Ecosystem Exchange (NEE). Leveraging a diverse array of data sources, including satellite measurements, infield sensor readings, and weather variables, the research seeks to comprehensively understand these changes. The core mission of this research initiative is to develop intuitive predictive solutions that can be disseminated to farmers and producers, thereby facilitating informed decision-making and promoting sustainable agriculture practices.
We will administer surveys to agriculturists to gain valuable insights into their perspectives and experiences. These surveys will delve into various aspects of agricultural practices, challenges faced, technological adoption, and preferences for support systems. By gathering feedback directly from agriculturists, we aim to better understand their needs and priorities, ultimately guiding the development of more effective and tailored solutions to enhance agricultural sustainability and productivity.
Our roadshows will serve as dynamic platforms to disseminate the findings and insights gathered from our research directly to agriculturists. Through engaging presentations, interactive sessions, and discussions, we will share key discoveries, innovative solutions, and practical recommendations tailored to address the challenges faced by agriculturalists. These roadshows will not only provide agriculturists with valuable knowledge and tools but also foster collaboration, networking, and knowledge exchange among peers and stakeholders within the agricultural community. By bringing research directly to the field, we aim to empower agriculturists with the information and resources needed to enhance their practices and promote sustainable agricultural development.
Coming Soon
In this coding challenge, participants will tackle real-world problems related to implementing Artificial Intelligence (AI) in agriculture to enhance outcomes. Agriculture is a vital sector globally, facing increasing challenges such as climate change, resource constraints, and growing demand for food production. AI technologies offer promising solutions to optimize various aspects of agriculture, including crop yield prediction, pest detection, soil health monitoring, and resource management.
Participants will be presented with a series of problems inspired by the practical challenges encountered in agricultural settings. These problems will require innovative thinking, algorithmic prowess, and proficiency in coding to develop effective AI solutions. Through this challenge, participants will not only gain hands-on experience in applying AI techniques to agriculture but also contribute to the advancement of sustainable farming practices.
The coding challenge will consist of several problem statements, each focusing on a specific aspect of agricultural optimization. Participants will be provided with datasets representing various agricultural parameters such as soil characteristics, weather patterns, crop types, and pest occurrences.
For information not covered here, please email disc@ou.edu.
Winning Teams
Drawing Winners
Gaming Keyboard, Mouse, Mouse Pad, Headphones: Caleb Furley
Nintendo Switch: Shyam Sundar Murali Krishnan
Motor Drone: Tamnoy Palit
Beats Solo Headphones: Kristiana Karshelieva
Sony Speaker: Vikash Prasad
Registration opens on 3/1/2024
Please note: Demographic, school, and major information on all participants will be needed at the time of registration.
If you would like to participate but are looking for a team, a slack channel has been created to help you communicate with others who are interested. You can join this channel by clicking here. This channel is not being moderated by DISC, it is up to individuals to find their teams.
Participating teams will receive access to a dedicated SharePoint folder, where they can securely store and manage their project documentation, including code files, datasets, and any other relevant materials. Within this shared space, teams can collaborate efficiently and ensure that all team members have access to the latest updates and contributions.
This structured approach to document management and submission timelines ensures transparency, organization, and adherence to the challenge guidelines, allowing for fair evaluation and feedback from the judges and challenge administrators.
Participants will present their solutions to a panel of judges and coding challenge administrators in a 15-minute presentation including Q&A. Presentations should effectively communicate the technical aspects of the solution, including algorithm design, implementation details, and performance metrics. Judges will evaluate presentations based on clarity, technical depth, innovation, and potential real-world applicability.
The challenge aims to foster innovation in AI applications for agriculture and inspire solutions that contribute to sustainable and resilient food systems while providing participants with an opportunity to showcase their skills and creativity in solving real-world problems.
Teams will receive a link to schedule a presentation before 4/15/2024.
Evaluation Rubric: View Rubric
Registration Opens:
Registration Closes:
Information Session:
Coding Challenge Begins:
Access to Data & Problem Statements:
Submit Extended Abstracts in Sharepoint:
Schedule Presentation Time:
Presentation Time Confirmation & Invites Distributed:
Presentations:
3/1/2024, 9:00 am CT
3/14/2024, 5:00pm CT
3/15/2024, 9:00 am CT
3/15/2024, 9:00 am CT
3/15/2024, 9:00 am CT
4/15/2024, 5:00 pm CT
4/15/2024, 5:00 pm CT
4/17/2022, 5:00 pm CT
Week of 4/22/2024
Winners will be announced on May 6, 2024. Winners will be listed here and will receive an email notification.
The winning team will be able to co-author at least one research paper.
First Place: $2000 Scholarship (split evenly between participants)
Second Place: $1000 Scholarship (split evenly between participants)
Third Place: $500 Scholarship (split evenly between participants)
3/12/2024 Update:
All participating team members, whose teams finish the challenge and presentations, will be individually entered into a raffle, to take place on May 6, 2024 for the following:
Beats Headphones (1)
Nintendo Switch (1)
Drone (1)
Gaming Keyboard & Mouse (1)
Bluetooth Speaker (1)
Coming Soon.
