Control of TDS Parameter Using IoT Technologies as a Factor in Improving Equipment Reliability and Cost-Efficiency

Abstract

This article presents a comprehensive Internet of Things (IoT) based solution for monitoring the efficiency of filtration systems based on the analysis of Total Dissolved Solids (TDS). The proposed system integrates a measuring device, a cloud-based IoT platform, and algorithms for filter condition assessment. The device performs TDS measurements before and after the filtration unit using a modified Gravity Analog TDS sensor, which operates by measuring the electrical conductivity of water using alternating current. Multiple measurements collected throughout the day are averaged and transmitted to the ThingsBoard platform, where the processing logic is implemented, including residual filter life estimation, efficiency evaluation, and automatic alert generation. The system architecture enables not only real-time water quality monitoring but also adaptive response to changes in operating conditions, improving the accuracy of filter degradation forecasting. This approach differs from traditional maintenance models that rely on fixed time intervals or consumption volumes, offering reduced operational costs, prevention of premature failures, and enhanced equipment reliability. A key feature of the system is the transition from local to centralized cloud-based data processing, which simplifies the scalability of the solution for large-scale, distributed infrastructures. The proposed design is particularly relevant for commercial equipment and industrial water treatment systems, where stable water quality and timely replacement of filtration components are critical.