Design and Development of an FPGA - Based Insitu Water Quality Monitoring System

There are two ways to measure and monitor water quality known as conventional method and real-time water quality method. The conventional method can be done by collecting the water samples and transfer them to the laboratory for testing the quality via different devices. However, this way of testing is cost and time consuming. In addition, it has lack of accuracy. While the other way of measuring water quality is done by integrating Internet of Things (IoT). This method could be done via using sensors and processors; therefore, it is preferable. This paper is generally concentrating on developing a multi-core reconfigurable Smart Water Quality System (SWQS) utilizing three sensors: pH, Total Dissolved Solids (TDS), and turbidity. The main objective of this article is present the work on developing a system-on-chip (SoC) design for SWQS on an FPGA. The FPGA-SoC has been used to parallelize the system?s operation to increase its performance. In this work an LCD display connected to a Raspberry Pi was used to display the data captured by the FPGA in real-time. The Quartus II software was used to maintain four cores using the platform designer. The programming for the sensors were done using the embedded C language on Eclipse tool. To verify the functionality of the system, different liquids have been used for testing. pH sensor has been verified using pure water, lemon juice and milk using a pH scale of 0 to 14 to determine acidity and alkaline. pH sensor showed a value of 7 for pure water as it is neutral solution, while the pH value for milk was 8 as it is base liquid. In addition, as lemon juice is acidic, therefore pH value was approximately 2. Additionally, verifying TDS sensor was done by adding salt to the water to measure dissolved solids. TDS values raised up to approximately 1800 ppm. Finally, the turbidity sensor revealed the dust inserted in the solution. The more dust in the liquid, the more TDS value there was recorded. Based on the results, the propose FPGA-based SWQStook 300ms for each ten readings when compared to 2s for each ten readings when using anArduino processor. This work has proven that an FPGA-SoC can be used as efficient heterogenous system.