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Team Grant

Sustainable Precision Aquaculture Network for Shellfish (SPANS)

oysters in boxes in water at an aquaculture farm
News Grand Challenges Grants Grand Challenges 2.0 Team Project Grants

Sustainable Precision Aquaculture Network for Shellfish (SPANS)

Grant Type: Team Grant
Topics: Food Security, Environment
Colleges Represented: ENGR, AGNR

Grand Challenges Grants

Summary

The Challenge:
The world faces a staggering challenge: feeding 10 billion people by 2050. Traditional protein sources often deplete our environment. Shellfish aquaculture offers a rare triple-win, including food security, water quality, and ecosystem health. As a nutritional superfood requiring zero feed or freshwater, oysters are the ocean’s natural engineers. They actively filter out excess nutrients to clean the water while building vital habitats for diverse marine life. While shellfish farming holds immense potential, our native oyster populations have collapsed. In the late 1800s, Maryland’s annual oyster harvest topped 15 million bushels. Today, despite significant restoration successes and recent growth, Maryland’s current oyster harvest remains at just 3-5% of that historic peak. To bridge this supply gap, the U.S. now imports over 8,000 tons of oysters annually. One of the primary barriers to expanding shellfish aquaculture is technology stagnation. While modern landbased farms have access to advanced precision farming tools, including sensors, robotics, and AI, underwater oyster farming has changed little in two centuries. Without real-time data on water quality or crop growth, planting and harvesting are imprecise and inefficient.


The Sustainable Precision Aquaculture Network for Shellfish (SPANS) is a strategic initiative to transform the shellfish aquaculture industry from an isolated, high-risk craft into a networked, digital powerhouse. SPANS employs state-of-the-art technologies, including robotics, AI, internet of things, and big data, to monitor underwater conditions and shellfish growth. SPANS provides farmers with actionable intelligence to reduce loss and optimize yields right on their phones. Ultimately, SPANS revitalizes coastal economies and strengthens global food security, while restoring clean water and healthy ecosystems. SPANS will: (1) Build new digital technology tools to help farmers; (2) Create a decision support system to guide farmers with precision farming and networked intelligence; (3) Put SPANS to work on real farms in the Chesapeake Bay to demonstrate how it helps increase harvests and save money; (4) Bring together farmers, engineers, scientists, and business experts to accelerate development, adoption, and commercialization.


SPANS is focused on transforming shellfish aquaculture into a reliable, scalable, high-tech solution to food insecurity, while promoting health of the planet and improving quality of life. SPANS turns struggling shellfish farming businesses into thriving, climate-resilient, data-driven enterprises. Intelligent farm management helps increase productivity and profitability. AI-enabled decision support provides early warning alerts to prevent mass die-offs due to climate stressors. Beyond farming, SPANS also helps enhance local biodiversity and water clarity in the long term. Furthermore, SPANS has the potential to create a new local industry that provides smart technology and data management services for farmers, bringing high-paying jobs to rural waterfronts. SPANS creates an international blueprint for Digital Restorative Aquaculture, setting a new global standard for how we interact with our oceans. SPANS also helps prove that AI and digital tools can be used to improve the planet, showing the world that farming can leave the environment cleaner than it was found. While the SPANS impact begins on farms, the ripple effects will improve the lives of millions of people. SPANS outcomes will include: smarter, cheaper nutrition, autonomous coastal protection, and digital economic equity.

Team Members:

PI: Miao Yu headshot PI: Miao Yu

Professor, Department of Mechanical Engineering, Institute for Systems Research, Maryland Robotics Center

ENGR
Co-PI: Nikhil Chopra headshot Co-PI: Nikhil Chopra

Professor and Director of Undergraduate Studies, Department of Mechanical Engineering, Department of Electrical and Computer Engineering, Institute for Systems Research, Maryland Robotics Center

ENGR
Co-PI: Yang Tao headshot Co-PI: Yang Tao

Fischell Family Distinguished Professor, Fischell Fellow, Fischell Department of Bioengineering, Maryland Robotics Center, Robert E. Fischell Institute for Biomedical Devices

ENGR
Co-PI: Hemendra Kumar headshot Co-PI: Hemendra Kumar

Precision Agriculture Specialist

AGNR
Co-PI: Matt Parker headshot Co-PI: Matt Parker

Principal Agent Associate

AGNR
Co-PI: Don Webster headshot Co-PI: Don Webster

Principal Agent, Wye Research and Education Center

AGNR