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Some materials can change their electrical polarization under the influence of a mechanical stress due to the piezoelectric effect. This stress-induced change in polarization produces a potential difference across the material. For this reason, the piezoelectric material generates an electrical signal when it is subjected to a pressure from acoustic energy. In this study, analysis of acoustic signals of footsteps from the piezoe-lectric sensor, especially for human footsteps, have been studied by considering the analytical relationship between the electrical signal generated from the sensor and the acoustic signal that provides the effect. We analyzed the acoustic signal data by assuming that the electrical output voltage of the piezoelectric sensor completely coincides with the frequency of the acoustic signals. The original signal was pre-processed using filtering systems and analyzed by the fast Fourier transform and power spectral density methods to extract descriptive spectral features of the signal. This preliminary study proposed a method as a sensor based piezoelectric security system to detect the acoustic signals that can indicate possible dangers to the safety of people or property. The source of the acoustic signal can be determined by matching it with the existing database using machine learning algorithms like face recognition systems for future goals.