Embedding Artificial Intelligence on Remote Underwater Sensor Nodes

将人工智能嵌入远程水下传感器节点

• 批准号: RGPIN-2021-03213
• 负责人: Bousquet, JeanFrancois
• 金额: $ 2.04万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742438
• 关键词: Embedding; Artificial; Intelligence; Remote; Underwater

As climate changes are becoming a global concern, the Earth's oceans can potentially offer solutions to mitigate the impact as they absorb 100 times more heat, and 50 times more carbon dioxide than atmosphere. As such, there is a strong desire to monitor subsea activity in harbours, along the North American coasts, and in target areas such as the Arctic, where there is increased shipping activity. Canada is a world leader in the development of ocean technology, since it is surrounded by three large bodies of water. To get access to the resources, it would greatly benefit from an infrastructure to monitor the activity below the ocean surface and effectively protect its assets for commercial, scientific and military applications. In this research program, a self reconfigurable sensor network is proposed and will be enabled using machine-to-machine communication between remote nodes that can be anchored to the sea bottom or embedded on autonomous underwater vessels. For this purpose, an infrastructure to enable the Internet of Underwater Things (IouT) must be considered. Acoustic propagation is the primary means to communicate between untethered nodes below the sea. However, its bandwidth is limited. With the deployment of heterogeneous sensors, bandwidth requirements are time varying. In this program, a scalable communication network will be enabled between distributed nodes underwater to ensure that a reliable end-to-end connectivity is maintained while optimizing the overall energy efficiency of the network. The network coverage depends highly on the status of the environmental conditions. Using complementary sensors that can infer the propagation conditions, the autonomous network will be self-configured depending on spontaneous demands from the network nodes. The potential for this network to produce massive data sets is significant and, as such, a multi-rate adaptive communication system will be defined to maintain connectivity. The underwater acoustic network will be deployed using custom transceiver nodes implemented on self-reconfigurable acoustic signal processing platform. Automated event identification and detection, as well as target tracking will be enabled at edge nodes, which will be responsible for preprocessing and sharing mission critical data. Finally, security features will be implemented on the sensor network to preserve data integrity and eliminate risks of intrusion. This research program will advance the complimentary fields of ocean technology and information and communication technology that are key to Canada's economy. In the long-term, a multi-node underwater communication network will be demonstrated using custom transceivers that are self-configurable. The testbed will serve to demonstrate the feasibility to deploy autonomous surveillance systems. The program will also train highly qualified personal who will promote the science internationally and who will be ready to enter the Canadian industry.

随着气候变化成为全球关注的问题，地球的海洋可以提供缓解影响的解决方案，因为它们吸收的热量是大气的100倍，二氧化碳是大气的50倍。因此，人们强烈希望监测港口、沿着北美海岸和北极等目标区域的海底活动，因为在北极，航运活动增加。加拿大是海洋技术发展的世界领导者，因为它被三大水体包围。为了获得资源，它将大大受益于监测海洋表面以下活动的基础设施，并有效保护其商业，科学和军事应用的资产。在这项研究计划中，提出了一种自重构传感器网络，并将启用远程节点之间的机器对机器通信，可以锚定到海底或嵌入在自主水下船只。为此，必须考虑实现水下物联网（IouT）的基础设施。声传播是水下无系留节点之间通信的主要手段。然而，它的带宽是有限的。随着异构传感器的部署，带宽需求是时变的。在该计划中，将在水下分布式节点之间启用可扩展的通信网络，以确保在优化网络整体能效的同时保持可靠的端到端连接。网络覆盖高度依赖于环境条件的状态。使用可以推断传播条件的互补传感器，自治网络将根据网络节点的自发需求进行自配置。该网络产生大量数据集的潜力是显著的，因此，将定义多速率自适应通信系统以保持连通性。水声网络将部署使用自重构声学信号处理平台上实现的自定义收发器节点。自动事件识别和检测以及目标跟踪将在边缘节点启用，这些节点将负责预处理和共享使命关键数据。最后，将在传感器网络上实施安全功能，以保持数据完整性并消除入侵风险。这项研究计划将推进海洋技术和信息通信技术的互补领域，这是加拿大经济的关键。从长远来看，多节点水下通信网络将使用自配置的定制收发器进行演示。该试验台将用于展示部署自主监视系统的可行性。该计划还将培养高素质的人才，他们将在国际上推广科学，并准备进入加拿大行业。