Implementación de filtros digitales para la eliminación de ruido en señales de sensores IoT

Abstract

Abstract: This thesis, "Implementation of Digital Filters for Noise Reduction in IoT Sensor Signals," focuses on the application of digital filters to minimize noise in IoT sensor signals. It begins with a bibliographic analysis of articles or papers on noise in these sensors and its negative impacts. Then, a methodology is proposed for the design, simulation, and implementation of various digital filters, including Median, Moving Median, Kalman, RLS, and Exponential Smoothing filters. Each filter is evaluated, considering its noise attenuation efficiency and its impact on the accuracy of the simulated data. It uses an open-source Python software environment for the implementation and testing of these filters. The study concludes with an assessment of the results obtained, evaluating them using various parameters or metrics and their importance in improving data quality in IoT systems, highlighting the need to select the most appropriate filter for each specific type of application.