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Descripción
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| This paper describes a proof of concept of a Fast-Data architecture to generate early response alerts on unforeseen events. For achieving that, in this work is presented the implementation of a fully integrated system capable to handle and process streaming data in order to generate an alert response for each generated event. The deployment stated are composed by a simulated wireless sensor network for generating environmental values, a centralized Kafka server for data segmentation and a machine learning model deployed in a Spark cluster for generating the emergency alerts. Also, a simulation was conducted assuming that a fire had affected the simulated scenario in order to determine and evaluate the system's behavior. Finally, the classification model is presented as an early system alternative based on real-time processing and can be used in different areas of occupational safety. | |
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Internacional
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Si |
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Nombre congreso
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2018 International Symposium on Networks, Computers and Communications (ISNCC) |
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Tipo de participación
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960 |
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Lugar del congreso
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Rome |
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Revisores
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Si |
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ISBN o ISSN
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978-1-5386-3779-1 |
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DOI
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10.1109/ISNCC.2018.8531069 |
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Fecha inicio congreso
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19/06/2018 |
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Fecha fin congreso
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21/06/2018 |
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Desde la página
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1 |
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Hasta la página
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6 |
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Título de las actas
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Proceedings of 2018 International Symposium on Networks, Computers and Communications (ISNCC) |