A. Sedunov, Christopher Francis, H. Salloum, A. Sutin, N. Sedunov
{"title":"Low-Size and Cost Acoustic Buoy for Autonomous Vessel Detection","authors":"A. Sedunov, Christopher Francis, H. Salloum, A. Sutin, N. Sedunov","doi":"10.1109/HST56032.2022.10025447","DOIUrl":null,"url":null,"abstract":"Achieving maritime domain awareness through the deployment of many low-cost, low-power sensors to monitor large ocean areas has become an international trend [1], [2], an approach known as “Ocean of Things” (OoT). The STAR Center at Stevens Institute of Technology is currently developing a sensor contained in a small, rapidly deployable “smart” buoy for automated detection of vessels by their underwater acoustic signatures. Designed with commercial off-the-shelf (COTS) components and materials, multiple such buoys can work together to form a large, distributed sensor network, periodically communicating data to a command center for analysis. Marine-traffic monitoring is of particular interest in areas where small-boat traffic is a security concern, but many existing systems for detecting such vessels can be difficult to deploy. The buoy is based on in-house manufactured hydrophones. Processing is performed on an ARM Cortex-M7 microcontroller. Methods were developed based on numerous past data collections by the Stevens Institute of Technology.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HST56032.2022.10025447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Achieving maritime domain awareness through the deployment of many low-cost, low-power sensors to monitor large ocean areas has become an international trend [1], [2], an approach known as “Ocean of Things” (OoT). The STAR Center at Stevens Institute of Technology is currently developing a sensor contained in a small, rapidly deployable “smart” buoy for automated detection of vessels by their underwater acoustic signatures. Designed with commercial off-the-shelf (COTS) components and materials, multiple such buoys can work together to form a large, distributed sensor network, periodically communicating data to a command center for analysis. Marine-traffic monitoring is of particular interest in areas where small-boat traffic is a security concern, but many existing systems for detecting such vessels can be difficult to deploy. The buoy is based on in-house manufactured hydrophones. Processing is performed on an ARM Cortex-M7 microcontroller. Methods were developed based on numerous past data collections by the Stevens Institute of Technology.
通过部署许多低成本、低功耗的传感器来监测大海域,实现海域感知已经成为一种国际趋势[1],[2],这种方法被称为“海洋物联网”(ocean of Things, OoT)。史蒂文斯理工学院的STAR中心目前正在开发一种传感器,该传感器包含在一个小型、可快速部署的“智能”浮标中,用于通过水下声学特征自动探测船只。采用商用现货(COTS)组件和材料设计,多个浮标可以一起工作,形成一个大型的分布式传感器网络,定期将数据传输到指挥中心进行分析。在小船交通是一个安全问题的地区,海上交通监测特别令人感兴趣,但许多现有的探测此类船只的系统可能难以部署。该浮标基于内部制造的水听器。处理在ARM Cortex-M7微控制器上执行。方法是根据史蒂文斯理工学院过去收集的大量数据制定的。