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primary topic: Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System

Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System
type: Thesis
type: Article
abstract: Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System Asep Denih1* , Muhammad Iqbal Suriansyah2 , Irwin Subarkah3 1,2,3 Department of Computer Science, Faculty of Mathematics and Natural Science, PakuanUniversity, Bogor, West Java, 16143, Indonesia Abstract Solar panels are the main component of a solar power generation system, converting sunlight into electrical energy. This study develops a solar cell monitoring method to collect output data in a specific text format and uses solar cell modules to maximize the efficiency of solar energy absorption that moves from east to west throughout the day. The solar panel tracking system uses the Raspberry Pi 4 as the central controller to follow the sun's movement. It is supported by LDR sensors to detect light intensity and move the panel according to the direction of light. In addition, the BH1750 and BME280 sensors are used to measure additional factors, such as temperature, wind pressure, humidity, light intensity, and light angle, that also affect the panels' power production. The collected data is processed using fuzzy logic to convert the exact values from the sensor into fuzzy data, allowing for more precise control in panel position optimization. The results showed that the system can improve the efficiency of solar energy absorption, with an optimal intensity level of 53,999.99 lux in very bright conditions and a fuzzy-lux difference of 1.1%, which is lower than previous research, indicating that the system is more efficient and supports accurate real-time monitoring. Keywords: BH1750; BME280; Fuzzy Logic; Raspberry pi; Solar Tracking System 1. Introduction A solar panel is the primary device of a solar power generation system [1], which generates electri
date: 2024-01-05
status: published
author list: authors
type: EPrint
type: ThesisEPrint
is part of: repository
has document: Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System (Text)
subject: Ilmu Komputer

Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System (Text)
type: Document
has file: Skripsi Irwin ( Fix ).pdf
has part: Skripsi Irwin ( Fix ).pdf

Universitas Pakuan
type: Organization

Fakultas Matematika dan Pengetahuan Alam, Universitas Pakuan
type: Organization

Muhammad Ikbal Suriansyah
type: Person
given name: Muhammad Ikbal
family name: Suriansyah

Asep Denih
type: Person
given name: Asep
family name: Denih

Irwin Subarkah
type: Person
given name: Irwin
family name: Subarkah

Fakultas Matematika dan Ilmu Pnegetahuan Alam
type: Organization

Program Studi Ilmu Komputer
type: Organization

HTML Summary of #9164 Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System
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primary topic: Improved Detection of Sunlight Source Determination Using Raspberry Pi 4-Based Fuzzy Logic on Solar Tracking System

Ilmu Komputer
type: Concept