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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Online Access: | http://dx.doi.org/10.1080/23311916.2019.1624287 |
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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 |
work_keys_str_mv |
AT suryonosuryono afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT ainiekhuriati afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT teddymantoro afuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT suryonosuryono fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT ainiekhuriati fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation AT teddymantoro fuzzyrulebasedfogcloudcomputingforsolarpaneldisturbanceinvestigation |
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1714828807885553664 |