Event detection in an audio-based sensor network

In this article we set out to examine whether analysis of the audio from a multimedia surveillance application can be used to augment an event detection system based on visual processing, and possibly contribute to any improvements. In processing audio information we are not concerned with identifying or classifying what type of event is detected as our aim is to keep audio processing to a minimum in order to allow deployment on a wireless sensor network. We describe an experiment where we gathered information from a series of traditional wired microphones installed in a typical surveillance setting. We also obtained information on activities carried out from cameras located in the same area. We present the results of analysis of audio information based on the mean of the volume, the zero-crossing rate, and the frequency and how these correlate with events detected visually. We found that detecting events, based on their volume only, returned satisfactory results. We show the results determined by applying this volume based approach to a range of physical environments.