Literature DB >> 31092957

StormSense: A New Integrated Network of IoT Water Level Sensors in the Smart Cities of Hampton Roads, VA.

Derek Loftis1, David Forrest2, Sridhar Katragadda3, Kyle Spencer4, Tammie Organski5, Cuong Nguyen6, Sokwoo Rhee6.   

Abstract

Propagation of cost-effective water level sensors powered through the Internet of Things (IoT) has expanded the available offerings of ingestible data streams at the disposal of 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 results of the new StormSense water level sensors to help establish the "regional resilience monitoring network" noted as a key recommendation from the Intergovernmental Pilot Project. To accomplish this, the 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 and radar remote sensing technologies to record water levels during 2017 Hurricanes Jose and Maria. These data were used to validate the inundation predictions of a street-level hydrodynamic model (5-m resolution), while the water levels from the sensors and the model were concomitantly validated by a temporary water level sensor deployed by the USGS in the Hague, and crowd-sourced GPS maximum flooding extent observations from the Sea Level Rise app, developed in Norfolk, VA.

Entities:  

Keywords:  Citizen Science; Global City Teams Challenge; Hurricane Jose; Hurricane Maria; Hydrodynamic Modeling; Internet of Things; King Tide; Replicability; Sea Level Rise; Smart City

Year:  2018        PMID: 31092957      PMCID: PMC6512834          DOI: 10.4031/MTSJ.52.2.7

Source DB:  PubMed          Journal:  Mar Technol Soc J        ISSN: 0025-3324            Impact factor:   0.708


  3 in total

1.  Wind disasters adaptation in cities in a changing climate: A systematic review.

Authors:  Yue He; Boqun Wu; Pan He; Weiyi Gu; Beibei Liu
Journal:  PLoS One       Date:  2021-03-17       Impact factor: 3.240

2.  A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks.

Authors:  Baiqian Shi; Stephen Catsamas; Peter Kolotelo; Miao Wang; Anna Lintern; Dusan Jovanovic; Peter M Bach; Ana Deletic; David T McCarthy
Journal:  Sensors (Basel)       Date:  2021-04-27       Impact factor: 3.576

3.  A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications.

Authors:  Daniel G Costa; Francisco Vasques; Paulo Portugal; Ana Aguiar
Journal:  Sensors (Basel)       Date:  2019-12-27       Impact factor: 3.576

  3 in total

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