WVU AI research could transform how scientists monitor ecosystems
West Virginia University researchers are integrating AI and edge computing into environmental sensors to process ecosystem data in near real time. This technology aims to eliminate the months-long latency currently required to analyze data from flux towers, allowing for faster responses to wildfires and droughts.
Why it matters
Improving the speed of environmental data analysis is critical for climate change mitigation and disaster response.
WVU researchers Steve Kannenberg and Jie Hu are using artificial intelligence and edge computing to process environmental data in near real time, helping scientists better understand how ecosystems respond to rapidly unfolding events like droughts and wildfires. (Submitted Photo)
With help from artificial intelligence, West Virginia University researchers are speeding up environmental scientists’ access to time-sensitive data about ecosystem health, allowing experts to respond rapidly to events like droughts or wildfires.
Supported by an Early-Concept Grant for Exploratory Research from the National Science Foundation, Steve Kannenberg , assistant professor of biology in the WVU Eberly College of Arts and Sciences , is integrating AI directly into local monitoring sensors to help scientists track ecosystem health in near real time.
Every day, forests, grasslands, and ecosystems around the world “breathe,” constantly trading carbon, water, and energy with the atmosphere, Kannenberg explained.
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