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

NSF 融合加速器轨道 E：融合全国智能精准水产养殖网络以实现可持续贝类养殖

• 批准号: 2137798
• 负责人: Miao Yu
• 金额: $ 75万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137798&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Towards

This convergence accelerator project is intended to address the sustainability issues 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 However, current domestic shellfish production is bottlenecked by outdated technology and tools.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, climate change, 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 climate change, and thus enhance production and sustainability. This convergent 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 potential for societal impact. 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.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.

该融合加速器项目旨在解决贝类水产养殖的可持续性问题。 作为沿海经济的重要驱动力，贝类养殖是最具生态可持续性的水产养殖形式。贝类水产养殖具有许多环境效益，贝类可以作为健康的蛋白质来源，增强人类健康。 然而，目前国内贝类生产因技术和工具落后而面临瓶颈。 许多贝类养殖方式效率低下、劳动密集型且破坏环境。对于海底牡蛎养殖来说尤其如此，在过去的 200 年里，这种养殖几乎没有发生什么变化。该融合加速器项目将开发全国智能精准水产养殖网络（SPAN）的新颖框架，以实现可持续的贝类生产，同时保护健康的海洋生态系统。从长远来看，该项目将解决联合国确定的全球粮食、气候变化和健康问题。 。计划中的教育工作将把慈善事业和社会变革作为科学和工程教育的核心价值，并促进多样性和包容性。这将有助于培养下一代劳动力，以推进网络蓝色经济并改善地球的健康和所有人的生活质量。SPAN框架将通过使用先进技术（例如物联网）支持的革命性概念来建立（物联网）、机器人技术和人工智能（AI））、生物学、环境科学和海洋科学方面的科学发现，以及利益相关者驱动的经济发展。 该项目将从根本上推动以下具体方向的研究边界：i）将建立物联网传感器网络，以提高未来贝类水产养殖的监测能力； ii）将开发基于机器人和自动化解决方案的新型智能精准收割工具，以提高农业效率和生产力，减少劳动力和能源使用，并最大限度地减少对环境的影响； iii) 将创建经验动态模型，以获得对生产与环境之间反馈的新理解，并进行生产预测； iv) 建立基于经济模型的优化框架，支持生产决策以获得环境和经济效益。 总的来说，这些研究活动最终将带来更好的农场管理、经济优化和更好地应对气候变化，从而提高产量和可持续性。这个融合加速器项目汇集了一支跨学科团队，他们在传感和成像、人工智能和计算机视觉、水下机器人和控制、贝类生物学、气候和海洋动力学和海洋学、环境经济学和水产养殖推广方面拥有丰富的专业知识，以及积极参与的利益相关者，追求具有高度社会影响潜力的研究。计划中的教育工作将把慈善事业和社会变革作为科学和工程教育的核心价值，并促进多样性和包容性。这将有助于培养下一代劳动力，以推进网络蓝色经济并改善地球健康和所有人的生活质量。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势进行评估，被认为值得支持以及更广泛的影响审查标准。