Self-Organizing Fuzzy Rule-Based Approach for Dealing with the Classification of Indoor Environments for IoT Applications

• Ualison Dias Universidade Federal de Juiz de Fora
• Michel Hell Universidade Federal de Juiz de Fora
• Álvaro Medeiros Universidade Federal de Juiz de Fora
• Daniel Silveira Universidade Federal de Juiz de Fora
• Eduardo de Aguiar Universidade Federal de Juiz de Fora

DOI: https://doi.org/10.5753/eniac.2019.9356

Abstract

Nowadays, a great part of the sensors used in the Internet of Things uses wireless technology in order to facilitate the construction of sensor networks. In this sense, the classification of the type of environment in which these sensors are located plays an important role in the performance of these sensor networks, since it leads to efficient power consumption when operating the deployed IoT sensors. Thus, this work presents an approach based on Self-Organizing Fuzzy Classifiers applied to indoor multipath environment classification from real-time measurements of the radiofrequency signal of a real wireless sensor network. Experimental results show that the proposed approach get high performance with low computational effort in the solution of the proposed problem.

Keywords: Classifier, Logic fuzzy, Self-organizing, Radiofrequency

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