NSF Convergence Accelerator Track E: Convergence Towards Nationwide Smart Precision Aquaculture Networks for Sustainable Shellfish Farming

This Convergence Accelerator project is intended to address the sustainability of shellfish aquaculture. As an important driver of the coastal economy, shellfish aquaculture is the most ecologically sustainable form of aquaculture. Shellfish aquaculture offers numerous environmental benefits, and shellfish can serve as a healthy source of protein to enhance human health.

However, current domestic shellfish production is bottlenecked by outdated technology and tools. Many shellfish farming practices are inefficient, labor intensive, and environmentally destructive. This is particularly true for on-bottom oyster farming, which has changed little in the past 200-years.

This Convergence Accelerator project will develop a novel framework on nationwide smart precision aquaculture networks (SPAN) to achieve sustainable shellfish production, while preserving healthy marine ecosystems. In the long term, this project will address the global issues of food, planetary resilience, and health as identified by the United Nations.

The planned education effort will bring philanthropy and social change as a core value for science and engineering education as well as promote diversity and inclusion. This will help prepare the next-generation workforce to advance the networked blue economy and to improve the health of the planet and quality of life for all.

The SPAN framework will be established by using revolutionary concepts empowered by advanced technologies (e.g., Internet of Things (IoT), robotics, and artificial intelligence (AI)), scientific discoveries in biology, environmental science, and ocean sciences, and stakeholder-driven economic development. The project will fundamentally push research boundaries in the following specific directions: i) IoT sensor networks will be established to advance the monitoring capabilities for future shellfish aquaculture; ii) Novel smart precision harvesting tools based on robotics and automation solutions will be developed to improve farming efficiency and productivity, reduce labor and energy usage, and minimize environmental impact; iii) Empirical dynamic models will be created to gain new understanding on feedback between production and environment, as well as to make production predictions; and iv) An optimization framework based on economic models will be established to support production decision-making to gain environmental and economic benefits.

Collectively, these research activities will ultimately lead to better farm management, economic optimization, and better coping with planetary resilience, and thus enhance production and sustainability. This Convergence Accelerator project brings together an interdisciplinary team with extensive expertise in sensing and imaging, AI and computer vision, underwater robotics and controls, shellfish biology, climate and ocean dynamics and oceanography, environmental economics, and aquaculture extension, along with readily-engaged stakeholders, in pursuit of research with high impact.

The planned education effort will bring change as a core value for science and engineering education as well as promote collaboration. This will help prepare the next-generation workforce to advance the networked blue economy and to improve the health of the planet and quality of life for all.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.