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Selected algorithms of MEMS accelerometers signal processing in burglary detector application


[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee

Year of publication


Published in

Poznan University of Technology Academic Journals. Electrical Engineering

Journal year: 2016 | Journal number: Issue 87

Article type

scientific article

Publication language


  • accelerometer sensor
  • data streaming
  • alarm system
  • artificial neural network

EN In the paper, implementations and results of operation of artificial neural network applied as a burglary classifier are presented in comparison to solution with a direct digital signal processing (DSP) approach. The neural network operates in a mobile access control device, that may be easily attached to a door. The device is an integrated system, equipped with several sensors based on microelectromechanical systems (MEMS) technology. Due to limited effectiveness of simple, conditional logic algorithms on acquired signal samples, a more sophisticated approaches are investigated. Data acquisition during imitation of various burglary scenarios and further processing of the recorded signals are described in the paper. Selection of the neural network structure and pre-processing methods of sensor signals are presented as well. The direct DSP algorithm based on the application of the properties of application phenomena is shown in the same way. Finally, results of selected algorithms implementation in a low-power 32-bit microcontroller system are presented. Limitation of the platform responsiveness in the real-time conditions and comparison of used classification methods are discussed in the paper conclusions.

Pages (from - to)

267 - 278

Presented on

Computer Applications in Electrical Engineering 2016, 18-19.04.2016, Poznan, Poland

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