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Faculty Profile

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Name: Emmanouil Anagnostou
Title: Professor
Affiliation:
Department: Civil & Environmental Engineering
E-Mail: manos@engr.uconn.edu
Personal/Lab Website: http://ucwater.engr.uconn.edu
Program/Department Website: http://www.engr.uconn.edu/cee/undergrad/admission/15-research/58-manos.html
Office Telephone: (860) 486-2298



Keywords | Categories: Civil and Environmental Engineering, damage modeling for electric distribution networks, data assimilation, Environmental Engineering, global precipitation measurement, hydro-meteorological modeling, numerical weather prediction, prediction of floods, remote sensing

Professional Summary

Intelligent Ambient Noise Sensors for Monitoring the Oceanic Environment: The sustainable protection and management of the oceans requires a comprehensive understanding of the processes and conditions that affect the state of the marine environment. To support this need, we are developing remote sensing techniques for smart detection and categorization of the ambient sounds into multiple sources, such as, environmental (rainfall and wind speed), anthropogenic (ships, drillings), biological (e.g. marine mammals) and geological (seismic activities, volcanic eruptions, landslides), and the quantification of the above mentioned classified sources.

Weather-Based Damage Prediction on Electric Distribution Network: New England is a densely forested region of the US, frequently affected by severe winds and precipitation that often leads to power outages. Our team is developing a weather-based power outage prediction system tailored for the Northeast Utilities service territories. The prediction framework utilizes forecasted values of meteorological parameters from a state-of-the-art numerical weather prediction model combined with infrastructure data and vegetation parameters to provide operational estimates of the number and spatial distribution of power outages over the region for an approaching weather event.