This session explores how water utilities can effectively use data, sensors, and AI to improve decision-making and operations. It begins with an overview of how to plan and implement end-to-end digital infrastructure, from IoT sensors and data communication to databases, analytics, and actionable insights, highlighting what it takes to build a strong foundation for advanced analytics. The session also includes a real-world case study from the City of Sugar Land, evaluating whether machine learning improves sewer pipe prioritization when using typical municipal datasets. The results highlight the importance of data readiness, problem definition, and evaluation metrics, showing that under common utility conditions, traditional methods can perform as well as or better than machine learning.

Speakers:

• Alence Poudel, PE – City of Sugarland
• Andrew Swirsky, PE – Infrasync

Registration and Sponsorship

WEAT Member Registration: Complimentary

Non-Member Registration: $85

Webinar Sponsorship: $300

Sponsorship includes your name and logo acknowledgment at the webinar, on the WEAT website, in the bimonthly Texas WET magazine, and on the WEAT social media pages.