Smart and Self-Sustaining Early Warning Systems for Coastal Flooding

Project Description

The University of Texas at San Antonio 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.

Basics

Nueces
University of Texas- San Antonio
28

Classification

CMP
  • 306
Coastal Hazards

Contacts

University of Texas- San Antonio
Chen Pan

Timeline

In Progress

Budget/Costs

$166,387.00