2026 ASEE Annual Conference & Exposition

Submersible sensor device and remote aquatic environment system for monitoring shallow water pollution

Presented at Ocean and Marine Division (OMED) Technical Session 1

Water is a vital natural resource for humans and living creatures. 97% of the Earth’s water can be found in oceans. The water can be found to be polluted in many different ways. The pollution of an aquatic environment, particularly at a specific site, can be a highly relevant topic for scientists and engineers. In this paper, a submersible sensor device as a part of a remote aquatic environment pollution monitoring system is presented. The remote aquatic environment pollution monitoring system can be used to collect water property data locally. The data collected from multiple locations can be analyzed to create predictive decisions through the neural network and machine learning analysis. A submersible water property sensor device is attached to the floating object and sends the data wirelessly. The collected data can be sent over the Internet to a web server such as Amazon Web Services (AWS). This is a multidisciplinary project with two departments of Engineering Technology and Ocean Engineering at Texas A&M University. The research has been conducted by engineering students, including a graduate student from the Electrical Engineering Department. This is a pilot research and development effort for further expansion with the potential involvement of more students. The submersible sensor device can measure water temperatures and light conditions at different depths to analyze the turbidity and cleanliness. In this paper, the submersible sensor device and aquatic environment pollution monitoring system will be introduced, and the educational values and lessons will be presented and discussed.

Authors

Dr. Byul Hur Texas A&M University [biography]

Dr. B. Hur received his B.S. degree in Electronics Engineering from Yonsei University, in Seoul, Korea, in 2000, and his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida, Gainesville, FL, USA, in 2007 and 2011, respectively. In 2016, he joined the faculty of Texas A&M University, College Station, TX. USA, where he is currently an Associate Professor. He worked as a postdoctoral associate from 2011 to 2016 at the University Florida previously. His research interests include Mixed-signal/RF circuit design and testing, measurement automation, environmental & biomedical data measurement, and educational robotics development.
Mr. Zhihao Pan http://orcid.org/0000-0002-8051-7979 Texas A&M University [biography]

Zhihao Pan is currently a PhD candidate in the Department of Electrical and Computer Engineering at Texas A&M University in College Station, Texas, USA. He earned his M.S. degree in Engineering Technology and his B.S. degree in Electronic Systems Engineering Technology from Texas A&M University. His research interests include RISC-V processor architecture, embedded systems, FPGA-based design, and hardware security.
Dr. Wei Zhan http://orcid.org/0000-0002-9956-1910 Texas A&M University [biography]

Dr. Wei Zhan is a Professor of Electronic Systems Engineering Technology and Associate Department Head for Undergraduate Studies at Texas A&M University. Dr. Zhan earned his D.Sc. in Systems Science and Mathematics from Washington University in St. Louis in 1991. From 1991 to 1995, he worked at University of California, San Diego and Wayne State University as a postdoctoral researcher and visiting assistant professor, respectively. From 1995 to 2006, he worked in the automotive industry as a system engineer. In 2006 he joined the Electronic Systems Engineering Technology faculty at Texas A&M. Dr. Zhan holds a joint appointment position in the department of Electrical and Computer Engineering at Texas A&M University. He is an American Society for Quality certified Six Sigma Black Belt and an ASQ Fellow. His research activities include control system theory and applications to industry, fault prognosis, system engineering, robust design, modeling, simulation, quality control, and optimization.
Prof. Mooh Kim Texas A&M University

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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