Extension of LoRa Coverage and Integration of an Unsupervised Anomaly Detection Algorithm in an IoT Water Quality Monitoring System

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:29:44Z
Fecha de publicación2023-01-01
ResumenHigh cost, long-range communication, and anomaly detection issues are associated with IoT systems in water quality monitoring. Therefore, this work proposes a prototype for a water quality monitoring system (IoT-WQMS) based on IoT technologies, which include in the system architecture a LoRa repeater and an anomaly detection algorithm. The system performs the data collection, data storage, anomaly detection, and alarm sending remotely and in real-time for the information to be captured by the multisensor node. The LoRa repeater allowed the spatial coverage of the LoRa communication to extend, making it possible to reach a place where originally there was no coverage with a single LoRa transmitter due to topography and line of sight. The prototype performed well in terms of packet loss rate, transmission time, and sensitivity, extending the long-range wireless communication distance. Indoor multinode testing validation for 29 days of the mean absolute error for average relative errors of water temperature, pH, turbidity, and total dissolved solids (TDS) were 0.65%, 0.30%, and 14.33%, respectively. The anomaly detector identified all erroneous data events due to node sensor recalibration and water recirculation pump failures. The IoT-WQMS increased the reliability of monitoring through the timely identification of any sensor malfunctions and extended the LoRa signal range, which are relevant features in the scope of in situ and real-time water quality monitoring.es_ES
Doihttps://doi.org/10.3390/w15071351es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/1729
Idiomaeses_ES
EditorialMDPI AGes_ES
RelaciónWateres_ES
URL relacionadohttps://doi.org/10.3390/w15071351es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteWater
TítuloExtension of LoRa Coverage and Integration of an Unsupervised Anomaly Detection Algorithm in an IoT Water Quality Monitoring Systemes_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorJáquez, Armando Daniel Blanco
AutorHerrera, María T. Alarcon
AutorCelestino, Ana Elizabeth Marín
AutorRamírez, Efraín Neri
AutorCruz, Diego Armando Martínez
AutorJáquez, Armando Daniel Blancoes_ES
AutorHerrera, María T. Alarcones_ES
AutorCelestino, Ana Elizabeth Marínes_ES
AutorRamírez, Efraín Neries_ES
AutorCruz, Diego Armando Martínezes_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número7es_ES
Rango de páginas1351es_ES
URL relacionadahttps://doi.org/10.3390/w15071351
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen15es_ES

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