Design, Development and Validation of an Arduino- Based Global System For Mobile Communication Prototype For Remote Water Level Monitoring

Abstract

Amidst global research on IoT-based water level monitoring devices, questions persist about sensor dependability and accuracy, especially in real-world scenarios. The research main objective was to design, develop and validate the Arduino-based Global System for Mobile Communication (GSM) prototype that utilizes a JSN-SR04T waterproof ultrasonic sensor in remote water level monitoring that meets the requirements of accuracy and reliability. Two theoretical frameworks were used in this research study to bring out the relationship between the predictor and outcome variables: The ultrasonic wave reflection principle and the Piezoelectric Effect. The research method employed in this research was mixed methods research comprising of explanatory and predictive statistical approaches of gathering and analyzing data to ascertain whether there was a significant difference between the means of data obtained from the IoT-based monitoring system and those from the manual gauge. Linear and Multiple regression were used to analyze the effect of air temperature variations on ultrasonic sensors under different locations. One (1) Arduino-based GSM water level monitoring prototype that utilized a JSN-SR04T waterproof sensor was developed and used to collect sensor datasets. The research study used stratified sampling techniques and had the following sample sizes: 48 manual gauge readings, 48 sensor readings and 15 tests of GSM efficiency. Data was visualized in the Arduino serial monitor, the ThingSpeak Server application and in Excel using graphs and charts. The research study found that the developed and validated Arduino-based GSM water level monitoring prototype was very accurate and reliable for application in water reservoir level monitoring. The IoT prototype achieved a water level accuracy of 98.92 percent in a lab setting environment and an accuracy of 95.083 percent in an outdoor simulation. The ANOVA test confirms the lack of significance for the location effect on accuracy with a p-value of 0.09099. While the sensor demonstrates high accuracy, reaching 100% in certain temperature ranges during outdoor testing, there are instances of lower accuracy, particularly noticeable at 23.44°C and 42.97°C. The impact of temperature on accuracy is evident, with fluctuations noted, and a distinct decrease in accuracy observed at higher temperatures. The research study concludes that while temperature significantly affects the accuracy of outdoor readings, the location of the sensor, whether indoors or outdoors, does not significantly influence accuracy. These findings provide valuable insights for optimizing sensor use in various environmental conditions. The significance of this research study is that it adds to the existing knowledge on effective water resource management through the implementation of IoT water level monitoring systems.