Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams

Understand

Remote sensors are becoming the standard for observing and recording ecological data in the field.

• Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access.
• Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial or total sensor failures.
• This means that the raw data stream must be cleaned before it can be used by domain scientists.