REAL-TIME ANOMALY DETECTION IN PRECIPITATION SENSORS

摘要: Recent advances in sensor technology are facilitating the deployment of sensors into the environment that can produce measurements at high spatial and/or temporal resolutions. Not only can these data be used to better characterize systems for improved modeling, but they can also be used to improve understanding of the mechanisms of environmental processes. With large volumes of data arriving in near real time, however, there is a need for automated anomaly detection to identify data that deviate from historical patterns. These anomalous data can be caused by sensor or data transmission errors or by infrequent system behaviors that may be of interest to the scientific or public safety communities. This study develops an automated anomaly detection method that employs a Dynamic Bayesian Network to assimilate data from multiple heterogeneous sensors into an uncertain model of the current state of the …