The wastewater monitoring and treatment system composed of both a monitoring project and treatment project. The monitoring project involved gathering data from Total Dissolved Solids, pH, and Dissolved Oxygen sensors and analyzing the data to detect any abnormalities. The treatment project used a bioabsorbent, silk fibroin film based sustainable water purification unit.
My assignment was to create a machine-learning model that could analyze water data and report any potential abnormalities. With almost all the existing data classified as normal, I decided to use a one-class support vector machine model to identify any abnormalities outside the normal range. I gathered the data sent from the Raspberry Pi on the robot to the Google Cloud server and created a normal range of values based on sensor and weather data.
