Collaborative Research: Ideas Lab: Smarter Microbial Observatories for Realtime ExperimentS (SMORES)

合作研究：创意实验室：用于实时实验的智能微生物观测站 (SMORES)

• 批准号: 2321651
• 负责人: Peter Girguis
• 金额: $ 59.52万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321651&HistoricalAwards=false
• 关键词: Collaborative; Research; Ideas; Lab; Smarter

Much of the ocean floor is covered with sediments that harbor large communities of animals, microscopic creatures, bacteria and archaea. These communities play a role in natural carbon cycling, yet there is a lot to learn about how this community nourishes the ocean, and stores carbon into deeper sediments. This Ideas Lab: Engineering Technologies to Advance Underwater Sciences (ETAUS) funded project will develop a new seafloor sensor/sampler system to study how tides affect the seafloor carbon cycle. It will also develop “smarter” control systems to make predictions about when and where to best collect samples. This would be a major improvement over existing approaches that waste battery power and have short deployment times. These advances will also provide broader impacts by providing technologies that can be applied to other sensor sets allowing them to record data for longer periods. The project provides mentoring and field opportunities to high-school and college students from a variety of backgrounds. The team will work with an award-winning filmmaker to produce a short documentary about careers in marine science.This project will develop a novel seafloor sensor/sampler array to better understand how tidal pumping and subsurface currents influence seafloor oxygenation and sedimentary carbon cycling. Equally important, it will develop control systems that use machine-learning models (MLM) to make informed predictions about when and where to best sense and sample based on historical and realtime data. The development of MLM controllers will enhance remote deployment, minimize excess power consumption and decrease the collection of sub-optimal samples. This project is funded jointly by the following NSF Divisions: Electrical, Communications & Cyber Systems, Environmental Biology, Ocean Sciences, and Civil, Mechanical & Manufacturing Innovation.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.

海底的大部分地区都覆盖着大量动物社区，微观创造物，细菌和古细菌的沉积物。这些社区在天然碳循环中发挥了作用，但是有很多关于这个社区如何滋养海洋的东西，并将碳存储到更深的沉积物中。这个想法实验室：推进水下科学（ETAUS）资助的工程技术将开发一个新的海底传感器/采样器系统，以研究潮汐如何影响海底碳循环。它还将开发“更聪明”的控制系统，以预测何时何地收集样品。这将是浪费电池电量且部署时间短的现有方法的重大改进。这些进步还将通过提供可以应用于其他传感器集的技术来提供更广泛的影响，从而使它们能够在更长的时间内记录数据。该项目为来自各种背景的高中生和大学生提供了心理和现场机会。该团队将与屡获殊荣的电影制片人合作制作有关海洋科学职业的简短纪录片。该项目将开发一个新型的海底传感器/采样器阵列，以更好地了解潮汐抽水和地下电流如何影响海底的氧合和沉积碳循环。同样重要的是，它将开发使用机器学习模型（MLM）的控制系统，以根据历史和实时数据对何时何地和何时含义和样本做出明智的预测。 MLM控制器的开发将增强远程部署，最大程度地减少多余的功耗并减少亚最佳样品的收集。该项目由以下NSF部门共同资助：电气，通信和网络系统，环境生物学，海洋科学以及民用，机械和制造业创新。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响审查审查标准来通过评估来诚实地支持。