FAMU’s GAEC-MSI focuses on integrating AI and geospatial tools into the curriculum, preparing students for careers in environmental sciences and bioinformatics.
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Announcement 📢 |
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We are excited to invite you and your students to participate in the Nexus Innovate Geospatial AI Workshop, a transformative learning experience designed to inspire the next generation of STEM leaders. This workshop will be held on Saturday, January 25, 2025, from 10 a.m. to 3 p.m. at Florida A&M University and aims to provide high school students with hands-on experience and exposure to advanced geospatial science and artificial intelligence technologies. ↓ LEARN MORE ↓ |
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The GAEC-MSI will integrate new geospatial tools (AI, machine learning, and IoT) to
address emerging areas in environmental engineering, bioinformatics, remote sensing,
and geospatial science to grow and strengthen recruitment and graduate progression
and training of geospatial professionals in an area of strategic emphasis in science,
technology, engineering, and mathematics (STEM).
The curriculum enhancement is transdisciplinary with a cadre of scientists and researchers
led by Victor Ibeanusi, Ph.D. FAMU-Dean School of the Environment in partnership with
Kentucky State University and Clark Atlanta University.
In an era of climate-induced environmental changes, finding innovative solutions to these challenges will depend on building a highly skilled and diverse workforce.
Geospatial AI is a digital brain trust focusing on the integration of new geospatial
tools (AI, machine learning, and IoT)) to better address emerging areas in environmental
engineering, bioinformatics, remote sensing, and geospatial science.
Our goal is to increase and strengthen recruitment and training of geospatial professionals.
Curriculum Innovation The intricate nature of environmental data presents considerable challenges for industry professionals. By equipping prospective and current environmental science students with training in cutting-edge software solutions and advanced AI methodologies, we can effectively convert real-world information into actionable insights. This includes examples like using Machine Learning (ML) and Computer Vision technologies to handle complex datasets detect illegal landfills through UAV imagery and video analysis or using AI tools to evaluate and forecast water quality. |
Workforce Development In addition to transforming current environmental science curriculum with these emerging
technologies, we believe exposing students earlier to this contributes to developing
a more robust pipeline of qualified talent for careers in environmental sciences.
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Geospatial AI comprises diverse faculty from multi-institutions and interdisciplinary academic fields, each with robust experience and expertise in transdisciplinary research and training, including geospatial data management, remote sensing, AI, and IOT, etc. These faculty members will collaborate with committed partners to integrate innovative research and education into innovative, contemporary, inclusive training to develop next generation graduates and future workforce fully capable of addressing pressing national needs in the DOE domains
Victor Ibeanusi, Ph.D.; Dh.c. (Honoris causa) is the Founder of the EnergyWaterFoodClimateNexus (EWFCN), a new science enterprise aimed at sustainable solutions for safe water, sustainable energy, food security, and climate resilience to expand the research frontier for new discoveries to the vexing challenges on our environment. [READ MORE...]
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The deployment of innovative AI-focused environmental science curricula, site visit opportunities to national laboratories, access to student coemptions and other virtual events will introduce students to an exciting, sustainable, innovative industry: one in which they can use their skills and have a positive impact on DOE. Partnering with Dept of Energy enables us to encourage networking, community building, and strengthening both for teacher training and student education.
Contacts:
Victor Ibeanusi, Ph.D.; Dh.c. (Honoris causa)
Victor.Ibeanusi@famu.edu
Joel Blount
Joel.Blount@famu.edu
This proposal highlights the value of intelligent novel spatial applications, complex data, and science-based decision-making capabilities for long-term ecosystem monitoring and restoration.
IoT devices can assist in data collection and monitoring in the field of bioinformatics.
For instance, IoT sensors can capture data from soils, plants and wildlife habitats,
to allow assessment of spatial and temporal patterns and changes. This data, when
combined with geospatial tools, can aid in cleanup activities, ecological research,
conservation efforts, and understanding the impact of environmental changes on biodiversity.
This curriculum will complement an existing concentration in the existing BS degree in Environmental Science offered in the School of the Environment. There are presently 5 Concentration areas for the BS in Environmental Science:
➜ Sustainability Science;
➜ Environmental Toxicology-Risk Assessment;
➜ Environmental Monitoring and Instrumentation;
➜ Environmental Restoration and Waste management;
➜ and Environmental Policy.
This new concentration area differs from these by focusing on the gathering and analysis of spatial data for a variety of environmental applications and related areas such as agriculture, natural resource management, and land use planning. Existing tracks do not include training in spatial analysis of large data sets, or acquisition of data by remote sensing, including drones, aircraft and satellite platforms. The new concentration area will include specialized training in geospatial science, remote sensing theory and methodology relative to applications in environmental science.
The curriculum in remote sensing will enable students to:
✔️ Explore utility of cloud-based geospatial environments (e.g., Google Earth Engine, Microsoft Azure- AI for Earth program) for cost-effective remote sensing and geospatial analysis.
✔️ Assist with development of landscape scale hydrologic assessments including processing of airborne LiDAR data and products for use in hydrologic models.
✔️ Development of novel, cost-effective techniques to monitor ecological and hydrologic change across relevant space and time scales within the Apalachicola region and Gulf coastal plain.
✔️ Explore utility of Drone Laser Scanning and Structure from Motion (SfM) techniques
to develop point clouds and related ecosystem and hydrologic structure products using
overlapping imagery from UAVs/drones, aircrafts and satellites.
✔️ Participate in the development of a regional geospatial decision support system (DSS)
to assess and prioritize ecological and hydrologic restoration needs.
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To show our appreciation for your commitment to Geospatial-AI education, we are pleased to offer the following incentives: |
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