IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 3; p. 842
• Main Authors: Campelo, José C, Capella, Juan V, Ors, Rafael, Peris, Miguel, Bonastre, Alberto
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22.01.2022; MDPI
• Subjects: Algorithms; Analytical chemistry; Cloud Computing; Communication; Communications networks; Correlation coefficients; Energy consumption; in-line monitoring; Internet of Things; Ion selective electrodes; ion-selective electrode; Monitoring; Monitoring systems; Potassium; potassium determination; R&D; Reproducibility of Results; Research & development; Sensors; smart sensor; Transducers; Water; water analysis; Wireless sensor networks; Wireless Technology; potassium determination; in-line monitoring; cloud services; ion-selective electrode; smart sensor; Internet of Things; water analysis
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22030842

The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.