Date of Award
Fall 12-1-2025
Document Type
Dissertation
Publication Status
Version of Record
Submission Date
December 2025
Department
Computer and Electrical Engineering and Computer Science
College Granting Degree
College of Engineering and Computer Science
Degree Name
Doctor of Philosophy (PhD)
Thesis/Dissertation Advisor [Chair]
Bing Ouyang
Abstract
Persistent monitoring in an aquatic environment is critical in many scientific and industrial applications. In-situ sensors that record water quality metrics, like dissolved oxygen, are essential in many aquaculture applications. Existing monitoring solutions can be cost prohibitive, difficult to maintain, and are typically deployed in fixed locations. This limits the usefulness of such systems in complex aquatic environments like coastal zones or pond aquaculture farms where bodies of water can be isolated from each other. In this dissertation research, an autonomous data collection framework is proposed to provide low-cost water quality monitoring through the combination of a variety of sensors and sensing platforms, such as waterproof UAVs and truck-based systems, that are optimized for in-situ sampling across disconnected bodies of water. Sensors and their platforms are connected to create an Internet of Things (IoT) sensor network for such environments. Sensor data collected from the system is transmitted and stored in a cloud database that provides users access to collected information via a web interface and text message alert system. To this end, this dissertation presents the methodology for designing optimal platforms, sensors, and their integration.
Recommended Citation
Fairman, William, "ROBOTIC MONITORING SYSTEM FOR COMPLEX AQUATIC ENVIRONMENTS" (2025). Electronic Theses and Dissertations. 188.
https://digitalcommons.fau.edu/etd_general/188