Master of Science (MS)
First Advisor's Name
Dr. Leonardo Bobadilla
First Advisor's Committee Title
Second Advisor's Name
Dr. Mark Finlayson
Second Advisor's Committee Title
Third Advisor's Name
Dr. Piero Gardinali
Third Advisor's Committee Title
Water Quality, Machine Learning, Sensing
Date of Defense
Water quality is a very active subject of research in the water science field, where its importance includes maintaining the environment, managing wastewater, and securing fresh water. However, the increase of human development has led to problems that are affecting the ecosystem. Motivated by these problems, this research aims to find a solution for understanding the coastal water of the Florida Keys. The research used machine learning methods to find a correlation between water quality dataset and profile measurements dataset. To achieve this objective, the research first went through cleaning, rescuing, and structuring a readable dataset of the profile measurements that could be used in the analysis. Once the profile measurements dataset was completed, the next step was to find the correlation. To get a correlation between two datasets, the research proposed the use of regression coefficients coming from four different measurements in the profile dataset. Then, the coefficients were clustered using k-means and an independency test was carried out on the two datasets. Lastly, the research also built a water drone in the form of an airboat, which can collect data and can be controlled through an android app.
Torres Castellanos, Alejandro M., "Correlating Water Quality and Profile Data in the Florida Keys using Machine Learning Methods" (2021). FIU Electronic Theses and Dissertations. 4693.
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