Progress 05/01/23 to 04/30/24
Outputs
Target Audience:K -12, faculty, staff, undergraduates, graduates, adminstration and local underserved farms. Changes/Problems:FY23 Yaser Banadaki left Southern University for another employment opportunity. Additionally, Steve Bovinoski was removed from the South Carolina State University and replaced with Dr. Joe Maja. Dr. Sudhir Trivedi (former Department head of Computer Science at Southern University). Dr. Trivedi has been formally appointed to assist the SU Ag Center. What opportunities for training and professional development has the project provided?A significant portion of time & effort during this reporting period was spent training at our partnering UC Davis AIFS and UD DSI. DSU established internal data science infrastructure to expand opportunities for student learning and research as well as to solve complex agricultural interdisciplinary challenges. Interdisciplinary courses are underway in the areas of data science and emerging technologies to introduce the E-IoT approach into the undergraduate curriculum. CoE E-IoT hosted research seminars to strengthen collaborations, spark innovation, and share findings. CoE E-IoT also engaged our collaborating institutions and organizations, including UC Davis AIFS and the UD Data Science Institute (DSI) and industry partners to invite new perspectives, tools, applications. Over the past year, CoE E-IoT faculty and scholars engaged in longitudinal training and education in the area of ET: Education & Workforce Develoment in Agriculture The CoE E-IoT mentorship plan employs a targeted, multi-level mentoring approach built on a solid research and extension foundation tailored to the unique needs of URMs in agriculture and related sciences. Key to the CoE E-IoT mentoring model is the inclusion of a URM Postdoctoral Research & Extension Fellow (Jamie Holmes). This critical role was designed to enhance the interactions between CoE investigators and strengthen the mentoring, guidance, communication between research groups, and dissemination of best practices. As outlined in our proposed work, CoE students will undertake training (hybrid/virtual) at the collaborating institutions (UC Davis AIFS and UD DSI) and conduct research activities at the respective 1890 institutions. CoE E-IoT intricately links our 1890 partners to recruit URMs in agriculture through a series of existing research and extension programs and financial incentives at the respective institutions. This is evidenced by the recruitment of (5) CoE URM undergraduates, (2) graduates and (1) postdoctoral associate thus meeting Goal 3. Implement high-impact practices that build a sustained pathway of scholars with workforce development skills deployable in emerging technologies and related disciplines - Objective 1: Recruitment and training of URM students (early college/ graduate/undergraduate/ postdoctoral). How have the results been disseminated to communities of interest?The inaugural black farmers conference highlighted key discussions, presentations, and outcomes of a gathering focused on agricultural issues and practices, attended by underserved farmers, industry experts, policymakers, and researchers. Key Elements: Theme and Focus: The central topic of the conference was focused on USDA/NRCS resources as well as specific challenges like climate change, sustainable farming, and emerging technologies to advance production. Keynote Speakers and Presentations: Highlights of key speeches and presentations, including insights from leading figures in the agricultural sector, researchers, and policy experts. Panel Discussions and Workshops: Summary of key takeaways from interactive sessions where participants discussed specific challenges, solutions, and best practices. Emerging Trends and Technologies: Discussion of new advancements in agricultural technology, practices, or research that were presented or discussed at the conference. Policy Implications: Analysis of how the conference addressed current policy issues affecting the agricultural sector, including potential impacts on farmers and the industry. Networking and Collaboration: Mention of opportunities for farmers to connect with peers, industry leaders, and potential partners for future collaboration. Call to Action: Any specific recommendations or next steps identified during the conference, whether for individual farmers, industry organizations, or policymakers. Emerging Farmers Conference Report: Focuses on the experiences and challenges of new and beginning farmers, highlighting workshops and discussions aimed at supporting their success. Conference Report: Summarizes research findings and advancements presented at a conference focusing on agricultural science and innovation. Farm Bill Conference Report: Updates on the Farm Bill, highlighting key policy decisions impacting agricultural sectors What do you plan to do during the next reporting period to accomplish the goals?FY24, will mark the hallmark of the Center of Excellence in Emerging Technologies Innovation Day that features Shark Tank-style pitches from diverse high- growth, early-stage startup founders who have developed new technology. Innovation Day provides a grand stage to showcase underrepresented entrepreneurs to potential investors, mentors, and the wider entrepreneurial community. Minority startups seek investments, forge partnerships, and gain vital support for their contributions to the innovation ecosystem. Innovation Day aims to address three core challenges in agriculture: 1. Educational Advancement: Developing co-curricular programming integrating AI, data science, and machine learning, preparing the next generation for advanced agricultural practices. The desired outcomes include: • Mastery of Technology Processes: Students will undergo rigorous training in state-of-the-art technology processes, enabling them to navigate and innovate within the digital landscape, which is essential for future careers in various tech-driven fields. • Understanding of Artificial Intelligence: The program will foster a deep understanding of artificial intelligence, from theoretical foundations to practical applications. Students will learn to develop AI-driven solutions, equipping them with the skills necessary to lead in AI-predominant industries. • Prototype Showcasing: Undergraduate and graduate students will have opportunities to design and showcase their prototypes, demonstrating their ability to apply learned concepts in real-world scenarios. This will enhance their learning experience and prepare them for entrepreneurial and innovative endeavors. 2. Inclusive Research and Workforce Development: Increasing the participation of underrepresented and disadvantaged groups through targeted training and tech transfer opportunities. 3. Technology Demonstration and Deployment: Showcasing practical applications of emerging technologies to revolutionize farming practices, enhance food production profitability, and improve resilience to climate change. Entrepreneurship and Innovation With training in advanced technologies, students can innovate and create startups focusing on smart agriculture solutions, precision farming, or sustainable agri-tech products. These entrepreneurial ventures will lead to generational wealth creation, not only for budding underrepresented entrepreneurs but also for low socioeconomic, disadvantaged communities Over the next year, the E-IoT Center will advance research and education in emerging technologies under the four (4) interdisciplinary research thrusts (IRT): 1) IRT1: "Integrating Emerging Technologies in Research and Education for Workforce Development; 2) IRT2: "Climate Smart Agriculture;" 3) IRT3: "Precision Agriculture and Livestock for Smart Farming;" and 4) IRT4: "Precision Food Processing and Sustainable Agricultural Systems. Initial steps will also be taken to establish an 1890 innovation ecosystem to accelerate emerging technologies. E-IoT will engage future leaders in identifying the skills and expertise that will drive the innovation and deployment of advanced tools and practices. In FY24, E-IoT will continue to establish mechanisms of integrating innovation into projects consisting of entrepreneurial activities, exposing scholars to transforming knowledge into products, designed with an eye toward implementation and their contribution to economic growth and innovation. The Center will continue to develop innovative communication pathways in dissemination of information, knowledge and proven agricultural technologies from extension agents, research centers/institutes, universities to farmers. It is imperative that these initial activities are continued to bridge the digital divide for communities in rural areas.
Impacts
What was accomplished under these goals?
Since receipt of the initial CoE E-IoT award, the team leaders have implemented targeted action steps toward Goal 1: Advance knowledge in Emerging IoT technologies using Data Science and AI approaches, which included the initial steps of convening the faculty of the proposed interdisciplinary research projects together to stem the collaborations that promotes the exchange of science across the 1890 institutions and disciplinary borders. The PIs/Co PIs have had monthly investigator meetings to prepare the distribution of the subawards and discuss the connections with OSP PoCs and the need for efficient reporting and financial management. The PI and Co-PIs have also had several meetings with 1890 Foundation leadership as well as numerous discussions with existing CoEs to gain lessons learned, assess the potential challenges and gain advice toward successful implementation of the CoE in Emerging Technologies based upon the experiences of the existing CoEs. During the initial year of implementation, the team convened the investigators from the various institutional projects under the proposed interdisciplinary research thrusts (IRT). Over the course of this fiscal year, the CoE leadership fostered collaborative research and training across the partner institutions to strengthen research capabilities in the area of emerging technologies. E-IoT initiated collaborative activities with our affiliate NSF funded UC Davis AI Institute for Next Generation Food Systems (AIFS) Institute and the University of Delaware Data Science Institute (DSI) to provide supplemental training opportunities and resources to support the Center research capacity building. Over the period of FY23, E-IoT leveraged ongoing research and training programs and resources to build an effective network of researchers and activities to increase interaction among research groups in agriculture and data-driven disciplines. E-IoT hosted our first series of guest lectures comprising subject matter experts in the area of emerging technologies in agriculture (Dr. Jayfus Doswell). The Center also commenced the training of investigators, students and extension specialists at our partnering AIFS and DSI Institutes. Monthly research hubs were convened to promote ideation and maintain communication among the Center scientists. Website development was completed within our initial months of funding to inform the general public of emerging technologies research and its applications. FY23activities included identification and support of undergraduate /graduate students at the respective 1890 institutions. During the course of the last reportingyear, the team engagedextension specialists in the deployment of Emerging Technologies to Local Minority, Underserved Farmers and Community Stakeholders. Extension specialist and students were trained and certified in FAA drone operations.Our IRTs focused on the user-inspired applications of data science and machine learning on existing datasets to educate research faculty and students as well as demonstrate ET in agriculture. Research groupshave been centered on the development of IoT techniques to enable an increase in agriculture production. As noted in the proposed work, CoE E-IoT will leveraging existing training and research programs to achieve Goal 1 "Integrating Emerging Technologies in Research and Education for Workforce Development." During this period of performance, CoE EIoT leveraged: UD NSF funded NRT- HDR: Computing and Data Science Training; HDR-DSC Delaware and Mid Atlantic Data Science Corp; NSF MRI: Acquisition of a Big Data and High Performance Computing System to Catalyze Delaware Research and Education Delaware Advanced Research Workforce and Innovation Network (DARWIN) and Data Science Institute (DSI) workgroups and training to the building of knowledge of data science (DS) and machine learning (ML) approaches in emerging technologies. CoE investigators and students employed IoT techniques via interdisciplinary research projects and collaborations that embody the ET approach in agriculture thus meeting Goal 1: 'Advance knowledge in Integrating Emerging Technologies in Research and Education for Workforce Development.' Objective 1. Build interdisciplinary research projects and collaborations that embodies the ET approach. IRT workgroups enabled students to work productively in teams led by faculty whose expertise covers the broad spectrum of emerging technologies in agriculture. CoE E-IoT hosted research seminars to strengthen collaborations, spark innovation, and share findings. CoE E-IoT also engaged our collaborating institutions and organizations, including UC Davis AIFS and the UD Data Science Institute (DSI) and industry partners to invite new perspectives, tools, applications. Over the past year, CoE E-IoT faculty and scholars engaged in longitudinal training and education in the area of ET.
Publications
|
Progress 05/01/22 to 04/30/23
Outputs
Target Audience:K -12, faculty, staff, undergraduates, graduates, adminstration and local underserved farms. Changes/Problems:Delaware State University much like the other Centers of Excellence struggled with the dispursement of the initial subaward funding which is being resolved. Nevertheless the Center was able to expend majority of our year 1 funds and have already initiated the dispursement of year 2 subawards. What opportunities for training and professional development has the project provided?A significant portion of time & effort during this reporting period was spent training at our partnering UC Davis AIFS and UD DSI. DSU established internal data science infrastructure to expand opportunities for student learning and research as well as to solve complex agricultural interdisciplinary challenges. Interdisciplinary courses are underway in the areas of data science and emerging technologies to introduce the E-IoT approach into the undergraduate curriculum. CoE E-IoT hosted research seminars to strengthen collaborations, spark innovation, and share findings. CoE E-IoT also engaged our collaborating institutions and organizations, including UC Davis AIFS and the UD Data Science Institute (DSI) and industry partners to invite new perspectives, tools, applications. Over the past year, CoE E-IoT faculty and scholars engaged in longitudinal training and education in the area of ET: Education & Workforce Develoment in Agriculture The CoE E-IoT mentorship plan employs a targeted, multi-level mentoring approach built on a solid research and extension foundation tailored to the unique needs of URMs in agriculture and related sciences. Key to the CoE E-IoT mentoring model is the inclusion of a URM Postdoctoral Research & Extension Fellow (Lindsey Hyppolite). This critical role was designed to enhance the interactions between CoE investigators and strengthen the mentoring, guidance, communication between research groups, and dissemination of best practices. As outlined in our proposed work, CoE students will undertake training (hybrid/virtual) at the collaborating institutions (UC Davis AIFS and UD DSI) and conduct research activities at the respective 1890 institutions. CoE E-IoT intricately links our 1890 partners to recruit URMs in agriculture through a series of existing research and extension programs and financial incentives at the respective institutions.This is evidenced by the recruitment of (5) CoE URM undergraduates, (2) graduatesand (1) postdoctoral associate thus meeting Goal 3. Implement high-impact practices that build a sustained pathway of scholars with workforce development skills deployable in emerging technologies and related disciplines - Objective 1: Recruitment and training of URM students (early college/ graduate/undergraduate/ postdoctoral). • Machine Learning with Python (Webinar) (March 2023) • Hands-on Data Science and Machine Learning Training Series (Network for Discovery and Learning Research, Purdue University (April 2023) • Oak Ridge and Los Alamos Labs and Sustainable Horizons Institute: Quantum Machine Learning Mini Conference (February 2023) • NSF MRI Workshop: Acquisition of a Big Data and High-Performance Computing System to Catalyze Delaware Research and Education • UD Data Science Institute (DSI)'s Delaware Advanced Research Workforce and Innovation Network (DARWIN) 2023 Computing Symposium • UD NSF funded NRT- HDR: Computing and Data Science Training for Materials Innovation, Discovery, Analytics (MIDAS) courses and community sessions 2023 • HDR-DSC Delaware and Mid Atlantic Data Science Corp advanced courses 2023 How have the results been disseminated to communities of interest?\Over the period of FY22, E-IoT leveraged ongoing research and training programs and resources to build an effective network of researchers and activities to increase interaction among research groups in agriculture and data-driven disciplines. E-IoT hosted our first series of guest lectures comprising subject matter experts in the area of emerging technologies in agriculture (Dr. Jayfus Doswell). What do you plan to do during the next reporting period to accomplish the goals?Over the next year, the E-IoT Center will advance research and education in emerging technologies under the four (4) interdisciplinary research thrusts (IRT): 1) IRT1: "Integrating Emerging Technologies in Research and Education for Workforce Development; 2) IRT2: "Climate Smart Agriculture;" 3) IRT3: "Precision Agriculture and Livestock for Smart Farming;" and 4) IRT4: "Precision Food Processing and Sustainable Agricultural Systems. Initial steps will also be taken to establish an 1890 innovation ecosystem to accelerate emerging technologies. E-IoT will engage future leaders in identifying the skills and expertise that will drive the innovation and deployment of advanced tools and practices. In FY23, E-IoT will establish mechanisms of integrating innovation into projects consisting of entrepreneurial activities, exposing scholars to transforming knowledge into products, designed with an eye toward implementation and their contribution to economic growth and innovation. The Center will continue to develop innovative communication pathways in dissemination of information, knowledge and proven agricultural technologies from extension agents, research centers/institutes, universities to farmers. It is imperative that these initial activities are continued to bridge the digital divide for communities in rural areas.
Impacts
What was accomplished under these goals?
Since receipt of the initial CoE E-IoT award (2022), the team leaders have implemented targeted action steps toward Goal 1: Advance knowledge in Emerging IoT technologies using Data Science and AI approaches, which included the initial steps of convening the faculty of the proposed interdisciplinary research projects together to stem the collaborations that promotes the exchange of science across the 1890 institutions and disciplinary borders. The PIs/Co PIs have had monthly investigator meetings to prepare the distribution of the subawards and discuss the connections with OSP PoCs and the need for efficient reporting and financial management. The PI and Co-PIs have also had several meetings with 1890 Foundation leadership as well as numerous discussions with existing CoEs to gain lessons learned, assess the potential challenges and gain advice toward successful implementation of the CoE in Emerging Technologies based upon the experiences of the existing CoEs. During the initial year of implementation, the team convened the investigators from the various institutional projects under the proposed interdisciplinary research thrusts (IRT). Over the course of this fiscal year, the CoE leadership fostered collaborative research and training across the partner institutions to strengthen research capabilities in the area of emerging technologies. E-IoT initiated collaborative activities with our affiliate NSF funded UC Davis AI Institute for Next Generation Food Systems (AIFS) Institute and the University of Delaware Data Science Institute (DSI) to provide supplemental training opportunities and resources to support the Center research capacity building. Over the period of FY22, E-IoT leveraged ongoing research and training programs and resources to build an effective network of researchers and activities to increase interaction among research groups in agriculture and data-driven disciplines. E-IoT hosted our first series of guest lectures comprising subject matter experts in the area of emerging technologies in agriculture (Dr. Jayfus Doswell). The Center also commenced the training of investigators, students and extension specialists at our partnering AIFS and DSI Institutes. Monthly research hubs were convened to promote ideation and maintain communication among the Center scientists. Website development was completed within our initial months of funding to inform the general public of emerging technologies research and its applications. FY22 activities included identification and support of undergraduate /graduate students at the respective 1890 institutions. The Center recruited (2) graduates, (5) undergraduates and (1) postdoctoral scholar during our initial year. During the course of the initial year, the team started the engagement of our extension specialists in the deployment of Emerging Technologies to Local Minority, Underserved Farmers and Community Stakeholders.? Over the course of year 1, the IRTs focused on the user-inspired applications of data science and machine learning on existing datasets to educate research faculty and students as well as demonstrate ET in agriculture. Over the last year, research in IRT1 has been centered on the development of IoT techniques to enable an increase in agriculture production. As noted in the proposed work, CoE E-IoT will leveraging existing training and research programs to achieve Goal 1 "Integrating Emerging Technologies in Research and Education for Workforce Development." During this period of performance, CoE E-IoT leveraged: UD NSF funded NRT- HDR: Computing and Data Science Training; HDR-DSC Delaware and Mid Atlantic Data Science Corp; NSF MRI: Acquisition of a Big Data and High Performance Computing System to Catalyze Delaware Research and Education Delaware Advanced Research Workforce and Innovation Network (DARWIN) and Data Science Institute (DSI) workgroups and training to the building of knowledge of data science (DS) and machine learning (ML) approaches in emerging technologies. CoE investigators and students employed IoT techniques via interdisciplinary research projects and collaborations that embody the ET approach in agriculture thus meeting Goal 1: 'Advance knowledge in Integrating Emerging Technologies in Research and Education for Workforce Development.' Objective 1. Build interdisciplinary research projects and collaborations that embodies the ET approach. IRT workgroups enabled students to work productively in teams led by faculty whose expertise covers the broad spectrum of emerging technologies in agriculture. CoE E-IoT hosted research seminars to strengthen collaborations, spark innovation, and share findings. CoE E-IoT also engaged our collaborating institutions and organizations, including UC Davis AIFS and the UD Data Science Institute (DSI) and industry partners to invite new perspectives, tools, applications. Over the past year, CoE E-IoT faculty and scholars engaged in longitudinal training and education in the area of ET:
Publications
|