Smart and Self-Sustaining Early Warning Systems for Coastal Flooding

Summary

Texas A&M University - Corpus Christi will develop smart and self-sustaining early-warning systems for coastal flooding with state-of-the-art low-power Tiny Machine Learning (TinyML) and energy harvesting solutions. The project will embed sensors, Tiny ML, and connectivity into energy-harvesting-powered devices for sustainable, accurate, and real-time monitoring, prediction, and pre-warning of flooding paths and risk levels.

View on Map

Basics

Nueces

N/A

Texas A&M University - Corpus Christi

$167,375

Classification

CMP 306

• Public Access
• Public Education & Outreach

Commencement of work on this project is contingent upon approval from the National Oceanic and Atmospheric Administration.

Timeline

10/01/23

Submitted

03/31/25

N/A

Funding Sources

Source 1

Coastal Management Program (CMP)

Primary

Federal

$99,819

28

2024

Source 2

Texas A&M University - Corpus Christi

Primary

Other

$67,556

Contacts

Texas A&M University - Corpus Christi

Dr. Chen Pan
Associate Professor
361.825.2448
Email

General Land Office

Coastal Resources
800.998.4456
512.475.0773