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SBIR Phase II: Real-Time Decision Making Software for Wastewater Treatment Operators

Project: Research

Abstract & Details

Description

Award ID: 2025902

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is the development of a real-time software for wastewater facilities to improve nutrient removal and recovery at reduced costs. The technology developed through this SBIR project will provide a proactive monitoring process that allows wastewater operators to observe and diagnose future process upsets, proactively mitigate underlying root causes, and prevent pollutant release without the use of expensive and environmentally damaging chemicals. Improvements in treatment effectiveness and reduction of operating and maintenance costs will limit the environmental impact of human activities, improve sustainability of wastewater treatment infrastructure, ensure public health, and reduce financial burdens associated with wastewater treatment. Following deployment individual facilities may see annual commercial savings upwards of $1.4 M per large facility from improved compliance and reduction in chemical costs in a wastewater services, a market opportunity estimated at upwards of $420 M in the United States. This project could lead to 35% improvement in regulatory compliance, 35% reduction in chemical treatment costs, and a guidance system for inexperienced operators in an industry expecting 50% of its operator workforce to retire over the next 5-10 years. In addition, the project will develop a game-based training program to train new operators in the skill sets to lead operation of sophisticated facilities. This SBIR Phase II project proposes to further the development of a software platform that uses available operational, biological, and meteorological data as inputs to deliver process forecasts and insights regarding biological phosphorus removal to operators. Machine-learning forecast models will be the basis of an attribution-based inference and decision-making system used for diagnosis and mitigation of upsets to the notoriously unstable biological phosphorus removal process. In this project, data systems of a full-scale wastewater facility will be synced with the software platform to deliver real-time results that will be evaluated over 12 months of pilot testing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Anna Brady-Estevez
StatusClosed
Effective start/end date08/15/2002/28/23

Funding

  • SBIR Phase II: $883,713.00

Active Fiscal Year

  • FY2023
  • FY2022

Start Fiscal Year

  • FY2020

TIP Programs

  • SBIR Phase II

Small Business

  • Yes

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 100%)

Technology Foci

  • Machine Learning Training Data
  • (confidence score: 91%)
  • Machine Learning (ML)
  • (confidence score: 97%)

Congressional District at Award

  • District n. 04 of Oregon

Current Congressional District

  • District n. 04 of Oregon

United States

  • Oregon

Core Based Statistical Area (CBSA)

  • Corvallis, OR

County

  • County: Benton, OR

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