Original Live Date: June 27, 2024 | | 2:00 PM EST/1:00 PM CST
Speaker: Curtis Smith
Credits: 0.1 CEU / 1.0 PDH / Approved for Envirocert International, Inc. (ECI) All Certifications: Approval # PDH-0036
Sponsors: Contech Engineered Solutions, Uni-Group, Timewell Drainage Products, Aqualis
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This presentation will showcase the latest techniques for real-time data collection and processing to help monitor the health of critical flood control assets like dams and levees. As remote data collection techniques improve and local data sensors become more plentiful, machine learning and data analytics can help predict the conditions that put flood control structures at risk. Additionally, we will review how flood control health monitoring can be tied with flood predictive services to provide risk feedback loop. Ultimately, this information is used as a decision support system to make risk-informed decisions more rapidly.
Learning Objectives
Upon completion of this presentation, attendees should be able to:
- Explain how the combination of data harvesting and machine learning can identify hazards at flood control structures faster than traditional predictive modeling methods.
- Discuss the future of this technology and how it will be applied to the AEC industry moving forward.
About the Presenter
![](https://stormwateruniv.com/wp-content/uploads/2024/05/hd_Smith_Curtis_clr_300px.jpg)
Curtis Smith is a Professional Engineer who serves as a team lead and technical expert for several clients in the flood risk industry, including FEMA. His projects are focused on leveraging data and statistics to identify flood-prone areas throughout the US and promote efficient solutions in floodplain management. Curtis’s expertise is in levee data analysis and watershed modeling, and his goal is to maximize value to the client by applying the latest approaches in cloud computing, statistics, computer science, and watershed modeling.
Sponsored by
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