West Virginia University researchers use AI to monitor ecosystems

Researchers at West Virginia University are utilizing artificial intelligence to accelerate access to time-sensitive environmental data. Supported by a National Science Foundation grant, assistant professor Steve Kannenberg and postdoctoral researcher Jie Hu are working to integrate AI directly into local monitoring sensors to track ecosystem health in near real time.

Currently, scientists studying ecosystem fluxes rely on eddy covariance towers, or flux towers, which use ultra-fast sensors to collect data on carbon, water, and energy exchanges. However, a significant bottleneck exists because the massive volume of data—collected 20 times per second—requires immense effort to quality control. This process often results in a latency of months or even years before usable data is available to the scientific community. By automating the filtering of sensor glitches and complex algorithms, this AI integration aims to allow experts to respond more rapidly to critical ecological events such as droughts and wildfires.