Automated Quality Control for a Weather Sensor Network
in
Workshop: Joint Workshop on AI for Social Good
Abstract
TAHMO (the Trans-African Hydro-Meteorological Observatory) is a growing network of more than 500 automated weather stations. The eventual goal is to operate 20,000 stations covering all of sub-Saharan Africa and providing ground truth for weather and climate models. Because sensors fail and go out of calibration, some form of quality control is needed to detect bad values and determine when a technician needs to visit a station. We are deploying a three-layer architecture that consists of (a) fitted anomaly detection models, (b) probabilistic diagnosis of broken sensors, and (c) spatial statistics to detect extreme weather events (that may exonerate flagged sensors).
Speaker bio: Dr. Dietterich is Distinguished Emeritus Professor of computer science at Oregon State University and currently pursues interdisciplinary research at the boundary of computer science, ecology, and sustainability policy.