Abstract
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.
Highlights
The Internet of Things (IoT) [1] is a concept that is being imposed at both social and scientific levels
Section 3.1.1 describes the part corresponding to the transducer (ISE) utilized, whereas Section 3.1.2 focuses on the rest of the elements that make up this device
Following our research line on the automation of chemical analysis systems and the application of new technologies and processes that allow both increases in their reliability and precision and improvements in their simplicity and cost, we are currently working on the monitoring of chemical parameters in lakes and rivers and, the evolution of the K+ concentration by using Ion Selective Electrodes (ISE) in these environments
Summary
The Internet of Things (IoT) [1] is a concept that is being imposed at both social and scientific levels. Emission spectroscopy techniques [17], such as flame photometry and inductively coupled plasma atomic emission spectroscopy (ICP-AES), are widely used for the analysis of potassium in water Their high prices and the complexity of instrumentation required make them unsuitable for in-line monitoring, for which the utilization of ion-selective electrodes (ISEs) is much more advisable. Our approach integrates ISE-based devices into a standard IoT platform and provides a new architecture of services and algorithms that process the data in order to improve their quality, increasing reliability and providing metadata on the temporal and space evolution of the measurements. The present paper reports the results of our current research to solve the proposed problem, which allows a step forward in chemical analysis monitoring systems to be taken This solution, applicable to other environments, allows the evolution from intelligent sensing nodes (information gathering) to intelligent sensing systems
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