PARTNER: ExPanding UCF AI Research To Novel Agricultural EngineeRing Applications (PARTNER) (2024)

Non Technical Summary
It is an urgent need to improve the career perception of the agricultural industry and inspire more people, especially younger generations, to join the US agricultural workforce. Meanwhile, AI research is being integrated into different sectors of agricultural production and processing with a high potential to fulfill the aforementioned need and spearhead the next agricultural industrial revolution. This project aims to establish a partnership between the AI Institute for Transforming Workforce & Decision Support (AgAID) and AI researchers at the University of Central Florida (UCF/AI) that builds on their complementary focus and strengths.The partnership will include a wide variety of activities including: (1) innovative AI methods and algorithms to potentially solve urgent issues in many agricultural field operations; (2) effective outreach and dissemination activities, such as education/training, workshop, technology demonstrations, and meetings, mutually benefiting AgAID and UCF/AI; and (3) human resource development through projects, courses, and mentoring activities hoping to inspire more researchers, educators, and students to conduct research or pursue graduate degrees in agricultural and biological engineering disciplines.This partnership not only brings about significant positive impacts for AgAID's agricultural research and UCF's efforts on AI for Agriculture, but also seeks to explore AI innovations with broad applicability across various societal domains such as aerospace and transportation.

Goals / Objectives
The goals of this multifaceted partnership are to jointly develop new AI technologies to address urgent issues in the agriculture industry, to engage a diverse pool of researchers and educators, to prepare students from various backgrounds to enter the U.S. agricultural workforce, and to stimulate Florida's high-tech economy.The detailed objectives of the project are:(i) Collaborative research projects will be conducted in AI driven methods for "motion control", "scheduling", "sensing", "manipulation", and "residue analysis". All of them and their corresponding AI innovations have been carefully selected and designed by the UCF/AI and AgAID researchers.(ii) Via a wide range of research, education/training, outreach, and dissemination activities, AgAID will expand its partnership to an HSI institution with a very large student population, extending its influence from the Midwest-West region to the Southeast region of the U.S.(iii) The UCF/AI-AgAID team will carry out many interwoven activities in the following categories: research, training/education, outreach, and development of AI capabilities and infrastructure.(iv) A diverse group of researchers and educators at UCF will be inspired to investigate AI-based solutions for addressing most pressing agricultural challenges aligned with AgAID objectives related to overcoming low efficiency of labor and farm management.

Project Methods
Efforts:The methods used in this partnership depend on specific activities.(1) In the proposed research projects, we anticipate that each AI method will advance its respective state-of-the-art models, tools and/or technologies.(2) In the proposed education and training program, we will co-develop a new cross-listed course combining agricultural engineering problems with new AI methods/algorithms.(3) In the proposed mentoring activities, we plan to hold frequent meetings, provide advises and suggest pathways to our participating undergraduate, graduate, and postdoctoral mentees. Participating students will gain training in theoretical studies, programming, experiments, writing, and presentation.(4) In the outreach and dissemination activities, a wide range of activities will be included such as summer exchange program, symposium, conference, ag shows, etc.(5) All partnership activities such as meetings and summer program will follow the "institute integration plan".Evaluation:Once the project starts, we will design a comprehensive evaluation plan to monitor and measure the progress in research, education/training, outreach and dissemination activities.We will collect the following data: hardware/software development, graduate careers, participants, and research impacts. For example, the research impacts will be evaluated based on the number and quality of publications and/or patents. Additionally, we will analyze the collaboration results among AgAID and UCF/AI researchers such as the impact of the AI research on AgAID projects and proposals spinning out of this partnership. We will also seek formal and informal feedback from growers and other stakeholders who attend our technology demonstration events, field days and targeted presentations. We will manage our project data according to our "data management plan".