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TrackingStorm: Visualization Tool for a Storm Detector Network (SDN) in the LF Spectrum
Atmospheric Electricity PhenomenaAdams, Augusto Mathias; Atmospheric Electricity PhenomenaHeilmann, Armando; Adams, Anselmo Daniel; Atmospheric Electricity PhenomenaDartora, César Augusto; Atmospheric Electricity PhenomenaOdake Junior, Edson Masao; Atmospheric Electricity PhenomenaTertuliano Filho, Horácio; Atmospheric Electricity PhenomenaSantos, Luis Augusto Cordeiro dos.
  • Atmospheric Electricity PhenomenaAdams, Augusto Mathias; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaAdams, Augusto Mathias. Curitiba. BR
  • Atmospheric Electricity PhenomenaHeilmann, Armando; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaHeilmann, Armando. Curitiba. BR
  • Adams, Anselmo Daniel; Eaatech Development LTDA. Department of Information Technologies. Curitiba. BR
  • Atmospheric Electricity PhenomenaDartora, César Augusto; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaDartora, César Augusto. Curitiba. BR
  • Atmospheric Electricity PhenomenaOdake Junior, Edson Masao; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaOdake Junior, Edson Masao. Curitiba. BR
  • Atmospheric Electricity PhenomenaTertuliano Filho, Horácio; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaTertuliano Filho, Horácio. Curitiba. BR
  • Atmospheric Electricity PhenomenaSantos, Luis Augusto Cordeiro dos; Federal University of Paraná. Group of Signal Propagation Systems. Atmospheric Electricity PhenomenaSantos, Luis Augusto Cordeiro dos. Curitiba. BR
Braz. arch. biol. technol ; 64(spe): e21210137, 2021. tab, graf
Artículo en Inglés | LILACS | ID: biblio-1285567
ABSTRACT
Abstract During the last year the Group of Atmospheric Electricity Phenomena (FEA/UFPR) developed a short range lightning location network based on a sensor device called Storm Detector Network (SDN), along with a set of algorithms that enables to track storms, determining the Wide Area Probability (WAP) of lightning occurrence, risk level of lightning and Density Extension of the Flashes (DEF), using the geo-located lightning information as input data. These algorithms compose a Dashboard called Tracking Storm Interface (TSI), which is the visualization tool for an experimental short range Storm Detector network prototype in use on the region of Curitiba-Paraná, Brazil. The algorithms make use of Geopandas and clustering algorithms to locate storms, estimate centroids, determine dynamic storm displacement and compute parameters of thunderstorms like velocity, head edge of electrified cloud, Mean Stroke Rate, and tracking information, which are important parameters to improve the alert system which is subject of this research. To validate these algorithms we made use of a simple storm simulation, which enabled to test the system with huge amounts of data. We found that, for long duration storms, the tracking results, velocity and directions of the storms are coherent with the values of simulation and can be used to improve an alert system for the Storm Detector network. WAP can reach at least 75% of prediction efficiency when used 6 past WAP data, but can reach 98.86% efficiency when more data is available. We use storm dynamics to make improved alert predictions, reaching an efficiency of ~87%.
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Texto completo: Disponible Índice: LILACS (Américas) Asunto principal: Alerta en Desastres / Sistemas Recordatorios / Tormentas / Accidentes por Descargas Eléctricas Tipo de estudio: Estudio pronóstico Idioma: Inglés Revista: Braz. arch. biol. technol Asunto de la revista: Biologia Año: 2021 Tipo del documento: Artículo País de afiliación: Brasil Institución/País de afiliación: Eaatech Development LTDA/BR / Federal University of Paraná/BR

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Texto completo: Disponible Índice: LILACS (Américas) Asunto principal: Alerta en Desastres / Sistemas Recordatorios / Tormentas / Accidentes por Descargas Eléctricas Tipo de estudio: Estudio pronóstico Idioma: Inglés Revista: Braz. arch. biol. technol Asunto de la revista: Biologia Año: 2021 Tipo del documento: Artículo País de afiliación: Brasil Institución/País de afiliación: Eaatech Development LTDA/BR / Federal University of Paraná/BR