A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation

The electrical energy produced by solar panel depends on the light intensity falling on the panel, but this process is prone to disturbances from external factors. Unfortunately, models of online solar panel disturbance diagnosis have not been widely developed. This research proposes a model of fog...

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Main Authors: Suryono Suryono, Ainie Khuriati, Teddy Mantoro
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Cogent Engineering
Subjects:
Online Access:http://dx.doi.org/10.1080/23311916.2019.1624287
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spelling doaj-22436d229eae42939acd7a9f7023eab72021-03-02T14:46:50ZengTaylor & Francis GroupCogent Engineering2331-19162019-01-016110.1080/23311916.2019.16242871624287A fuzzy rule-based fog–cloud computing for solar panel disturbance investigationSuryono Suryono0Ainie Khuriati1Teddy Mantoro2Diponegoro UniversitySampoerna UniversitySampoerna UniversityThe electrical energy produced by solar panel depends on the light intensity falling on the panel, but this process is prone to disturbances from external factors. Unfortunately, models of online solar panel disturbance diagnosis have not been widely developed. This research proposes a model of fog computing using fuzzy rule-based algorithm is capable of automatic monitoring and diagnosing factors affecting solar panel efficiency. Data from physical parameter of sensors are acquired by the System on Chip (SoC) Wi-Fi microcontroller and sent to the fog server via a Wi-Fi gateway. The fuzzy rule-based algorithm consists of investigation rules showing the relationships among efficiency, light intensity, output electrical power, temperature, and humidity. Output of fog network computing is sent to the cloud server and serves as information for users of this investigation system. The fog network system is able to improve cloud performance, in terms of the transmission time has increased performance from 246.1 to 27.9 ms. In general, this system is able to improve relative efficiency of solar panel by 2.1%, compared to solar panels not equipped with this instrument. In order to obtain accurate investigation results, detailed conditions of all possible events in the field are required.http://dx.doi.org/10.1080/23311916.2019.1624287solar paneldisturbancewireless sensor systemfuzzy rule-basedefficiency
collection DOAJ
language English
format Article
sources DOAJ
author Suryono Suryono
Ainie Khuriati
Teddy Mantoro
spellingShingle Suryono Suryono
Ainie Khuriati
Teddy Mantoro
A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
Cogent Engineering
solar panel
disturbance
wireless sensor system
fuzzy rule-based
efficiency
author_facet Suryono Suryono
Ainie Khuriati
Teddy Mantoro
author_sort Suryono Suryono
title A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
title_short A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
title_full A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
title_fullStr A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
title_full_unstemmed A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
title_sort fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
publisher Taylor & Francis Group
series Cogent Engineering
issn 2331-1916
publishDate 2019-01-01
description The electrical energy produced by solar panel depends on the light intensity falling on the panel, but this process is prone to disturbances from external factors. Unfortunately, models of online solar panel disturbance diagnosis have not been widely developed. This research proposes a model of fog computing using fuzzy rule-based algorithm is capable of automatic monitoring and diagnosing factors affecting solar panel efficiency. Data from physical parameter of sensors are acquired by the System on Chip (SoC) Wi-Fi microcontroller and sent to the fog server via a Wi-Fi gateway. The fuzzy rule-based algorithm consists of investigation rules showing the relationships among efficiency, light intensity, output electrical power, temperature, and humidity. Output of fog network computing is sent to the cloud server and serves as information for users of this investigation system. The fog network system is able to improve cloud performance, in terms of the transmission time has increased performance from 246.1 to 27.9 ms. In general, this system is able to improve relative efficiency of solar panel by 2.1%, compared to solar panels not equipped with this instrument. In order to obtain accurate investigation results, detailed conditions of all possible events in the field are required.
topic solar panel
disturbance
wireless sensor system
fuzzy rule-based
efficiency
url http://dx.doi.org/10.1080/23311916.2019.1624287
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