Originally Aired - Wednesday, October 9 • 8:30 AM - 10:00 AM Central Time
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Location: New Orleans Convention Center, Room 253
Title: Leveraging Machine Learning for Facility Operations
Description:
Three case studies on employing machine learning (ML) and artificial intelligence will be featured during this interactive session. Case studies from multiple facilities that have leveraged ML to improve operations and reduce costs will be highlighted. Attendees will also consider factors that impact successful deployment of a ML system at their facility.
Learning Objectives
Interactive Session | Case Study Analysis
At the end of this session, participants will be able to:
1. Compare how changes to reinforcement learning control impacts the ability to successfully train a machine learning agent for optimized treatment.
2. Determine if a machine learning optimization solution is appropriate for a WRRF and which one(s) would be most applicable to a facility.
3. Identify the level of effort to build, deploy, and maintain machine learning models in the cloud with an understanding of financials, risks, benefits, and skillset.
PRESENTATIONS
Understanding the Potential for Reinforcement Learning-Based WRRF Control Optimization
8:30 AM - 8:50 AM
Group Analysis: Understanding the Potential for Reinforcement Learning-Based WRRF Control Optimization
8:50 AM - 9:00 AM
Market Analysis of WRRF Real-Time, AI-Driven Optimization Solutions
9:00 AM - 9:20 AM
Group Analysis: Market Analysis of WRRF Real-Time, AI-Driven Optimization Solutions
9:20 AM - 9:30 AM
Utilizing Intelligent O&M to Harness Machine Learning Across the Water and Wastewater Industry
9:30 AM - 9:50 AM
Group Analysis: Utilizing Intelligent O&M to Harness Machine Learning Across the Water and Wastewater Industry
9:50 AM - 10:00 AM
Type: Interactive Technical Session
