Open AccessA data estimation for failing nodes using fuzzy logic with integrated microcontroller in wireless sensor networks
Author(s) -
Saad Al-Azzam,
Ahmad Sharieh
Publication year - 2020
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v10i4.pp3623-3634
Subject(s) - backup , computer science , wireless sensor network , missing data , fuzzy logic , microcontroller , node (physics) , real time computing , table (database) , computer data storage , data transmission , lookup table , data mining , embedded system , computer hardware , computer network , database , engineering , operating system , structural engineering , artificial intelligence , machine learning
Continuous data transmission in wireless sensor networks (WSNs) is one of the most important characteristics which makes sensors prone to failure. a backup strategy needs to co-exist with the infrastructure of the network to assure that no data is missing. The proposed system relies on a backup strategy of building a history file that stores all collected data from these nodes. This file is used later on by fuzzy logic to estimate missing data in case of failure. An easily programmable microcontroller unit is equipped with a data storage mechanism used as cost worthy storage media for these data. An error in estimation is calculated constantly and used for updating a reference “optimal table” that is used in the estimation of missing data. The error values also assure that the system doesn’t go into an incremental error state. This paper presents a system integrated of optimal data table, microcontroller, and fuzzy logic to estimate missing data of failing sensors. The adapted approach is guided by the minimum error calculated from previously collected data. Experimental findings show that the system has great potentials of continuing to function with a failing node, with very low processing capabilities and storage requirements.