StormSense:沿海洪水预报信息和自动警报信息系统的蓝图

J. Loftis, S. Katragadda, S. Rhee, Cuong Nguyen
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引用次数: 6

摘要

通过物联网(IoT)通信的低成本水位传感器的可用性增加,扩大了现代智慧城市可用的公共可摄取数据流的范围。StormSense是一项基于物联网的洪水预测研究计划,也是全球城市团队挑战赛的积极参与者,该挑战赛旨在加强弗吉尼亚州汉普顿路智能城市的洪水准备工作,以应对风暴潮、降雨和潮汐导致的洪水。在这项研究中,我们通过使用新的StormSense水位传感器,提出了一个蓝图和一系列适用的协议,以帮助建立一个区域弹性监测网络。为了进一步推动这一努力,弗吉尼亚联邦中心的潮汐监测潮汐预报系统被用作一个起点,将整个地区现有的(NOAA)和新的(USGS和StormSense)水位传感器整合起来,并在汉普顿路的纽波特纽斯、诺福克和弗吉尼亚海滩等城市展示解决方案的可复制性。VA. StormSense的网络采用超声波声纳和雷达遥感技术的组合来记录水位,并通过使用三个独立的云环境开发自主警报信息系统。一个用于管理水位监测传感器和警报消息传递,一个用于运行模型并与后处理结果接口,另一个用于在地理空间上呈现洪水结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
StormSense: A Blueprint for Coastal Flood Forecast Information & Automated Alert Messaging Systems
Increased availability of low-cost water level sensors communicating through the Internet of Things (IoT) has expanded the horizons of publicly-ingestible data streams available to modern smart cities. StormSense is an IoT-enabled inundation forecasting research initiative and an active participant in the Global City Teams Challenge seeking to enhance flood preparedness in the smart cities of Hampton Roads, VA for flooding resulting from storm surge, rain, and tides. In this study, we present the a blueprint and series of applicable protocols through the use of the new StormSense water level sensors to help establish a regional resilience monitoring network. In furtherance of this effort, the Virginia Commonwealth Center for Recurrent Flooding Resiliency's Tidewatch tidal forecast system is being used as a starting point to integrate the extant (NOAA) and new (USGS and StormSense) water level sensors throughout the region, and demonstrate replicability of the solution across the cities of Newport News, Norfolk, and Virginia Beach within Hampton Roads, VA. StormSense's network employs a mix of ultrasonic sonar and radar remote sensing technologies to record water levels and develop autonomous alert messaging systems through the use of three separate cloud environments. One to manage the water level monitoring sensors and alert messaging, one to run the model and interface with the post-processed results, and one to geospatially present the flood results.
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