Applications of Defense Technologies to the Fisheries

国防技术在渔业中的应用

• 批准号: 9360489
• 负责人: Patrick Simpson
• 金额: $ 6.5万
• 依托单位: Scientific Fishery Systems, Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-03-15 至 1994-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9360489&HistoricalAwards=false
• 关键词: Applications; Defense; Technologies; Fisheries

9360489 Simpson Fisheries have become an increasingly more significant food source. Currently 30% of the protein consumed by Americans comes from the sea and this percentage is growing. Over the past decade fisheries have experienced more regulation because of bycatch -- that portion of a fisherman's catch that is not the primary target. Because of the increased regulation caused by bycatch, fisheries management has become increasingly more difficult. Techniques that can automatically and non-intrusively detect, classify, and quantify fish populations are of intense interest to all levels of fisheries management. Technologies are needed to improve the ability of fisheries management to monitor the fisheries. One area that will immediately benefit the fisheries is a more efficient and effective technique automatically to detect and classify fish. A sonar system with these capabilities does not currently exist. The transition of Anti-Submarine Warfare (ASW) sonar signal classification technology to fisheries would be of great benefit to American Fishing fleets, American fisheries management groups, and to our dwindling American manufacturing base. Scientific Fishery Systems, Inc. (SFS) is developing a fish detection and classification system that utilizes these defense technologies.

9360489辛普森渔业已成为越来越重要的食物来源。 目前，美国人消耗的蛋白质中有30%来自海洋，而且这一比例还在上升。 在过去的十年里，渔业经历了更多的监管，因为副渔获物-渔民捕获的那部分不是主要目标。 由于混捕造成的管制增加，渔业管理变得越来越困难。 能够自动和非侵入性地检测、分类和量化鱼类种群的技术对各级渔业管理都具有浓厚的兴趣。 需要技术来提高渔业管理部门监测渔业的能力。 一个将立即使渔业受益的领域是自动检测和分类鱼类的更高效和有效的技术。 目前还不存在具有这些能力的声纳系统。 反潜战（ASW）声纳信号分类技术向渔业的过渡将对美国渔船队、美国渔业管理团体和我们日益减少的美国制造业基地大有裨益。 科学渔业系统公司(SFS)正在开发一种利用这些防御技术的鱼类检测和分类系统。