WaterWise
AI-powered irrigation recommendations built on physics-informed neural networks, designed for diverse agricultural contexts worldwide.
Precision irrigation, powered by AI
WaterWise is an AI-powered irrigation recommendation app that uses physics-informed neural networks (PINNs) and stochastic differential equations to generate field-specific water usage recommendations. It integrates with NASA SMAP satellite soil moisture data and is designed to work across diverse agricultural contexts in 10+ languages.
The underlying framework uses model predictive control to optimize water delivery. Simulations show a projected 22.3% reduction in water usage compared to standard irrigation schedules.
Launch Video ↗Three steps to smarter irrigation
Input Your Field Data
Enter your crop type, field size, and location. WaterWise pulls NASA SMAP satellite soil moisture data automatically for your region.
AI Analyzes Conditions
Our physics-informed neural network processes soil moisture, weather patterns, and crop-specific parameters to model optimal water needs.
Receive Recommendations
Get actionable irrigation recommendations in your language. No technical expertise required, because WaterWise handles the science.
Award-winning science
AMS Karl Menger Award
3rd place special award from the American Mathematical Society, recognizing the spectral-stochastic mathematical framework underlying WaterWise.
Congressional Recognition
WaterWise won first place in Kentucky's 2nd Congressional District and was recognized by Rep. Brett Guthrie for its work in water conservation technology.
Recognized by the U.S. Congress
WaterWise was selected as the winner of the Congressional App Challenge for Kentucky's 2nd Congressional District. The app received formal recognition from Representative Brett Guthrie (KY-02), who highlighted its potential impact on water conservation and agricultural efficiency.
The Congressional App Challenge is a nationwide competition that recognizes outstanding student-built applications. WaterWise was chosen from entries across the district for its technical innovation and real-world applicability.
