Sensor Data Analysis Using Moving Average Filter and 256-Point FFT for Wireless Sensor Networks
Mayur Chauhan, Pratik Thorwe, Monodeep J. Mukherjee, Y. Srinivas Rao · 2018
Wireless Sensor Networks (WSNs) are in demand in numerous fields recently and are evolving in terms of efficiency day by day. WSNs however face problems such as latency while dealing with large data values in the sensor nodes. Therefore we propose an algorithm for fast and meaningful analysis of data values for the nodes in the WSNs. We utilize a moving average filter which is a finite impulse response filter and 256-point Fast Fourier Transform in our algorithm which is simulated using MATLAB 2018a and tested with values of accelerometer and gyroscope from STM32L475VGT6 microcontroller based system. The algorithm is also applied for border security management system with addition of camera surveillance feature for better security purpose and General Packet Radio Service(GPRS) services using GSM/GPRS module for transmission of sensor or camera based data to dedicated entities regarding intrusion at borders.