CIVIC-PG Track A: Machine Learning Approaches to Improve Resilience of Water Utilities to — NSF Award to Johns Hopkins University
The objective of this Civic Innovation Challenge (CIVIC) project is to support research on design and implementation of a machine learning (ML)-based system, called WAUTO (Water operations AUTOmation), to optimize wastewater treatment plant operations during extreme weather events. Working with the Little Patuxent Wast
| Award title | CIVIC-PG Track A: Machine Learning Approaches to Improve Resilience of Water Utilities to |
|---|---|
| Award ID | 2431342 |
| Awardee | Johns Hopkins University |
| City | BALTIMORE |
| State | MD |
| Amount obligated | $75,000 |
| Principal investigator | Yinzhi Cao |
| Program | S&CC: Smart & Connected Commun |
| Start date | 10/01/2024 |
| Abstract | The objective of this Civic Innovation Challenge (CIVIC) project is to support research on design and implementation of a machine learning (ML)-based system, called WAUTO (Water operations AUTOmation), to optimize wastewater treatment plant operations during extreme weather events. Working with the Little Patuxent Wastewater Reclamation Plant (LPWRP), researchers from the Johns Hopkins University Applied Physics Laboratory (APL) and the Whiting School of Engineering (WSE) aim to enhance LPWRP’s |
| Source | NSF Awards |
$799/mo
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