课题基金 / 基金详情

Project MARLIN (Maritime, Acoustic, Realtime, Learning, Information and Notification)

Project MARLIN (Maritime, Acoustic, Realtime, Learning, Information and Notification)
MARLIN 项目(海事、声学、实时、学习、信息和通知)
批准号:
10065619
负责人:
金额:
$90.67万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
利用英国首创的科学发展,我们将开发一种颠覆性的水下监听方法,这将彻底改变我们对英国领海的监控和警务方式。通过与南安普顿大学声音与振动研究所(ISVR)的合作,我们正在开发新的机器学习(ML)技术,使实时详细监测远程海洋中的人类,动物和环境活动成为可能。我们还在开发一种颠覆性的方法,将海洋传感器与新的近地轨道卫星和5G连接起来,促进海上宽带物联网(IOT)。RS Aqua作为水下噪声记录技术和海洋监测系统的领先供应商在国际上享有盛誉,而ISVR在将ML应用于水下噪声分析方面拥有国际领先的专业知识。该项目将开发新一代RS Aqua水下噪声记录仪,该记录仪可以在现场内部处理大型声学数据集,并通过智能手机网络应用程序将宽带信息发送给最终用户。除此之外,ISVR的博士后职位将使用新的水下数据集(由RS Aqua记录)来开发将在水下记录仪上运行的新的自我学习ML过程。最终目标是开发一种可以停泊在世界任何地方的水下仪器,并快速学会识别不寻常的环境有害活动。它将把有关该活动的宽带信息发送到一个网络应用程序,这样利益相关者和管理者就可以实时做出决定。这项技术有可能彻底改变近海能源、政府机构、非政府组织和国防部门监测和管理英国海洋环境的方式。
英文摘要
Using scientific developments pioneered in the UK, we will develop a disruptive method of listening underwater that will revolutionise how we monitor and police the UK's territorial waters.In partnership with the Institute of Sound and Vibration Research (ISVR) at the University of Southampton, we are developing new machine learning (ML) techniques which make possible detailed monitoring of human, animal and environmental activity in the remote ocean in real time. We are also developing a disruptive method of connecting ocean sensors to new low earth orbit (LEO) satellites and 5G, facilitating a broadband internet of things (IOT) at sea.RS Aqua has an international reputation as a leading provider of underwater noise recording technology and oceanographic monitoring systems, and ISVR has leading international expertise in the application of ML to underwater noise analysis. The project will develop of a new generation of RS Aqua underwater noise recorders which can internally process large acoustic datasets in situ and send broadband information to the end users via a smartphone web application. Alongside this, a postdoctoral role at ISVR will use new underwater datasets (recorded by RS Aqua) to develop new _self-learning_ ML processes which will run on the underwater recorders.The end goal is to develop an instrument that can be moored underwater, anywhere in the world, and quickly learn to identify environmentally harmful activities that are out of the ordinary. It will send broadband information about that activity to a web app, so stakeholders and managers can take decisions in real time. This technology has the potential to revolutionise how offshore energy, government agencies, NGOs, and the defence sector monitor and manage the UK ocean environment.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金