SBIR Phase I: Scaling Ocean Observation with Millions of In Situ Sensors

SBIR 第一阶段：利用数百万个原位传感器扩展海洋观测

• 批准号: 2014968
• 负责人: David Mann
• 金额: $ 22.5万
• 依托单位: Loggerhead Instruments
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014968&HistoricalAwards=false
• 关键词: SBIR; Phase; Scaling; Ocean; Observation

The broader impact/commercial potential of this SBIR Phase I project is to benefit from a global network of proposed sensors continuously monitoring the world’s oceans at unprecedented scale. The need for better ocean sensing will benefit weather forecasting and fisheries management. Predicting hurricane strength is difficult when the heat content of the ocean is not measured at high resolution. In addition, many fisheries are showing signs of change as fish migrate towards the poles. This project will provide ocean temperature data to weather forecasters, as well as information about commercially important fish species. Applications include academia, government, fisheries, maritime shipping, energy, and the military. This SBIR Phase I project will scale ocean observation by developing the technology required to enable deployment millions of inexpensive smart platforms (surface drifters and profiling buoys) using acoustics, motion sensors and AI to detect marine animals, track vessels, and measure oceanographic conditions. This project will develop and test low power, efficient artificial intelligence (AI) algorithms to detect boats on a bottom-stationing profiler. This bottom-stationing profiler is designed to rest on the bottom to hold station, and then rise to the surface to transmit boat detection information over a satellite to a cloud computing system. This project includes a demonstration of monitoring boat visitation rates at artificial reefs in Florida.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.

SBIR第一阶段项目的更广泛的影响/商业潜力是受益于一个全球传感器网络，以前所未有的规模持续监测世界海洋。对更好的海洋传感的需求将有利于天气预报和渔业管理。当海洋的热含量没有以高分辨率测量时，预测飓风强度是困难的。此外，随着鱼类向两极迁移，许多渔业正在显示出变化的迹象。该项目将向天气预报员提供海洋温度数据，以及关于重要商业鱼种的信息。 应用包括学术界，政府，渔业，海运，能源和军事。该SBIR第一阶段项目将通过开发所需的技术来扩大海洋观测，以部署数百万个廉价的智能平台（表面漂移器和剖面浮标），使用声学，运动传感器和人工智能来检测海洋动物，跟踪船只和测量海洋条件。该项目将开发和测试低功耗，高效的人工智能（AI）算法，以检测底站剖面仪上的船只。这种底部定位剖面仪的设计是停在底部保持位置，然后上升到水面，通过卫星将船只探测信息传输到云计算系统。该项目包括在佛罗里达人工鱼礁监测船只访问率的示范。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估的支持。