Burglary detection based on accelometric data using selected signal processing algorithms

The paper presents two approaches to the problem of burglary detection. The first one utilizes direct signal processing, while the other – artificial neural network (ANN). Both algorithms are compared in real operating conditions. The implementation of the algorithms was performed in a portable, battery operating devices that can be easily attached to the door. For direct comparison, two identical devices including several MEMS accelerometers and 32 bit microcontroller have been used – each with one algorithm implemented. The goal of using artificial neural network algorithm was to improve the performance of the burglary detection system in comparison to classical direct signal processing. The structure of ANN and required pre – processing of the input data, is presented and discussed as well. The article also describes the research system required to collecting the data for ANN training and to directly compare both algorithms. Finally, the results of behavior of the classification methods in real actual conditions is discussed.