IoT-Based Portable Autonomous Surface Vehicle for Comprehensive Hydrological Water Quality Monitoring System with Fish-Finder

Technological advancement plays an essential part in addressing environmental problems such as water quality monitoring. The study designed and implemented an Unmanned Surface Vehicle for Water Quality Monitoring with Fish Finder. The USV was equipped with a navigation control system that can be either remote-controlled or autonomous. The sensing system of the USV was composed of five parameters, including a fish finder, pH sensor, EC sensor, TDS sensor, and temperature sensor. The Pixhawk Controller was the USV’s navigation and data communication system, it did all the central control for the operations required for autonomous and remote-controlled navigation. The five parameters were attached to the linear actuator for the up-and-down mechanism. Percentage Accuracy and Root Mean Squared Error (RMSE) were used as the statistical method to model the relationship between a dependent variable and one or more independent variables, predict the sensor readings based on a known standard, such as a measurement taken with a highly accurate instrument from the Biolab, and compares the predicted values with the actual readings from the sensor and statistics. Percentage Accuracy Values were, Fish Finder = 86%, pH = 95%, Temperature = 97%, EC = 76%, TDS = 76%. Root mean squared error (RMSE) determined how well the model fits the data and how accurate the sensor readings were. Fish Finder RMSE = 0.24, pH RSME = 0.089, EC RSME = 0.26, TDS RSME = 0.57, Temperature RSME = 0.13. The data points on the graph form an almost straight line, indicated the linear relationship between the actual readings of the water and the readings obtained by the sensor.