J3 Applications of Artificial Intelligence to the Coastal Environment II

Monday, 13 January 2025: 1:45 PM-3:00 PM
218 (New Orleans Ernest N. Morial Convention Center)
Hosts: (Joint between the 23rd Symposium on the Coastal Environment; and the 24th Conference on Artificial Intelligence for Environmental Science )
Cochairs:
Philippe E. Tissot; Gregory Dusek, NWS, Silver Spring, MD and Peyman Taeb

This session will explore Machine Learning and Big Data applications in the coastal environment. Abstracts are invited on the following topics: the collection of novel, large data sets for data-driven modeling; descriptive modeling of data in the coastal environment, including processing, quality control and event detection or classification; predictive modeling in the coastal environment, including time series, deep learning, tree-based, neural network, and related approaches; the development and application of explainable AI methods and the development and assessment of trust in coastal AI methods.

Papers:
1:45 PM
J3.1
Deployment of Lower Cost Water Level Sensors and Machine Learning Models for Local Coastal Inundation Monitoring and Predictions
Jacob Alonzo, Texas A&M Univ.-Corpus Christi, Corpus Christi, TX; and P. E. Tissot, A. Beasley, M. Vicens-Miquel, R. Shelly, and F. Tissot

2:00 PM
J3.2
Enhancing Coastal Resilience Using Hyperlocal Water Level Sensor Networks and AI
Ryan T Searcy, Hohonu, Inc., Honolulu, HI; and K. Mukai, O. Wattenmaker, and B. Glazer

2:15 PM
J3.3
Using Machine Learning for Enhanced Seasonal Water Level Predictions in the Great Lakes
Yi Chen, Michigan Technological University, Houghton, MI; Michigan Technological University, Houghton, MI; and P. Xue and C. Wang

2:30 PM
J3.4
Data-Driven Methods for Ocean Surface Wave Measurements in the Coastal Arctic Using Submarine Fiber Optic Cables
Jacob Davis, University of Washington, Seattle, WA; and J. Thomson and M. Smith

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner