SBIR Phase II: Ubiquitous Flood Forecasting using Sensors and Analytics

NSF Award Search · 01002526DB NSF RESEARCH & RELATED ACTIVIT · $1,244,153 · view on nsf.gov ↗

Abstract

The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to enhance US flood preparedness with real-time monitoring and forecasting. Flash floods are among the most destructive and costly natural disasters in the United States, causing billions of dollars in damage each year. Using sensors and data, this project will advance knowledge to deliver localized, 24-hour forecasts at the scale of municipal infrastructure, allowing emergency responders to take proactive measures before floods escalate. The resulting technology will help stormwater managers mitigate damage, improve public safety, and allocate resources more effectively. The innovation will also drive economic growth by fostering a new market for smart urban water management solutions, creating jobs in the water sector, and positioning the U.S. as a leader in flood forecasting technology. By improving accessibility to high-quality flood prediction tools, this project will help communities of all sizes to build resilience against severe weather events. This Small Business Innovation Research (SBIR) Phase II project will investigate a novel flood forecasting system that combines real-time sensor data with advanced analytics to provide actionable insights for stormwater managers. The research will focus on three core objectives: (1) synthesize an automated methodology to infer urban drainage connectivity using publicly available geospatial data, (2) implementing a predictive flash flood

Key facts

NSF award ID
2450595
Awardee
HYFI LLC (MI)
SAM.gov UEI
M6EMDBJ9RHR6
PI
Brandon P Wong
Primary program
01002526DB NSF RESEARCH & RELATED ACTIVIT
All programs
ARTIFICIAL INTELL & COGNIT SCI, Big Data Science &Engineering
Estimated total
$1,244,153
Funds obligated
$1,244,153
Transaction type
Cooperative Agreement
Period
06/15/2025 → 05/31/2027