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

dc.contributor.authorBlanco Jáquez, Armando Daniel
dc.contributor.authorAlarcón Herrera, María Teresa
dc.contributor.authorMarín Celestino, Ana Elizabeth
dc.contributor.authorNeri Ramírez, Efrain
dc.contributor.authorMartínez Cruz, Diego Armando
dc.date.accessioned2024-05-30T21:28:47Z
dc.date.available2024-05-30T21:28:47Z
dc.date.issued2023
dc.identifier.citationJáquez, A.D.B.; Herrera, M.T.A.; Celestino, A.E.M.; Ramírez, E.N.; Cruz, D.A.M. Extension of LoRa Coverage and Integration of an Unsupervised Anomaly Detection Algorithm in an IoT Water Quality Monitoring System. Water 2023, 15, 1351. https://doi.org/10.3390/w15071351
dc.identifier.urihttp://hdl.handle.net/11627/6590
dc.description.abstractHigh 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.
dc.publisherMDPI
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectLoRa
dc.subjectAnomaly detection
dc.subjectWater quality
dc.subjectIoT
dc.subjectReal-time monitoring
dc.subject.classificationECOLOGÍA
dc.titleExtension of LoRa Coverage and Integration of an Unsupervised Anomaly Detection Algorithm in an IoT Water Quality Monitoring System
dc.typearticle
dc.identifier.doihttps://doi.org/10.3390/w15071351
dc.rights.accessAcceso Abierto


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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