ANFIS Analysis of Wireless Sensor Data with FPGA

Year 2018, , 22 - 32, 26.06.2018

Khazal Ahmed Tuncay Ercan

https://doi.org/10.30801/acin.357635

Abstract

Applications
related with WSNs may include thousands of separate sensor nodes, production
and control data for different industrial sectors. It is important to manage
these applications, monitor the network and reprogram the nodes to avoid
operational problems. In this study, we propose a smart wireless sensor network
using a reconfigurable embedded system of Field-Programmable Gate Arrays
(FPGAs) with a soft-core processor. This processor can be programmed
dynamically and synthesized to implement the preprocessing of sensed data by
ensemble Hybrid Neuro-Fuzzy algorithms such as Adaptive Neuro-Fuzzy Inference
System (ANFIS). The first part of the proposed work is based on Matlab software
to develop and train the ANFIS algorithm. Two different types of data sets
(temperature and humidity) downloaded from Internet have been used in order to
make a comparison between the Matlab Toolbox and modified ANFIS algorithm with
momentum factor. The results obtained in this study have shown that the
modified ANFIS algorithm is the convenient choice in terms of speed, accuracy.

Keywords

ANFIS, Neuro-Fuzzy System, FPGA, Sensor Nodes, Smart Node

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