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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Autores principales:	Suryono Suryono, Ainie Khuriati, Teddy Mantoro
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	solar panel disturbance wireless sensor system fuzzy rule-based efficiency Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/22436d229eae42939acd7a9f7023eab7
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id	oai:doaj.org-article:22436d229eae42939acd7a9f7023eab7
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spelling	oai:doaj.org-article:22436d229eae42939acd7a9f7023eab72021-11-04T15:51:56ZA fuzzy rule-based fog–cloud computing for solar panel disturbance investigation2331-191610.1080/23311916.2019.1624287https://doaj.org/article/22436d229eae42939acd7a9f7023eab72019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1624287https://doaj.org/toc/2331-1916The 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.Suryono SuryonoAinie KhuriatiTeddy MantoroTaylor & Francis Grouparticlesolar paneldisturbancewireless sensor systemfuzzy rule-basedefficiencyEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	solar panel disturbance wireless sensor system fuzzy rule-based efficiency Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	solar panel disturbance wireless sensor system fuzzy rule-based efficiency Engineering (General). Civil engineering (General) TA1-2040 Suryono Suryono Ainie Khuriati Teddy Mantoro A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation
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.
format	article
author	Suryono Suryono Ainie Khuriati Teddy Mantoro
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
publishDate	2019
url	https://doaj.org/article/22436d229eae42939acd7a9f7023eab7
work_keys_str_mv	AT suryonosuryono afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT ainiekhuriati afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT teddymantoro afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT suryonosuryono fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT ainiekhuriati fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT teddymantoro fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation
_version_	1718444701123608576

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

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