Implementation of Fuzzy Logic for Early Warning System for Flood Disaster in Cilacap District

Indonesia's tropical climate and high rainfall frequently lead to unnoticed river overflows, causing significant health and economic losses. A Flood Early Warning System (EWS) using LoRa communication and an Arduino Mega2560 microcontroller was developed, incorporating ultrasonic, DHT11, rain gauge, and anemometer sensors to measure water level, temperature, humidity, rainfall, and wind speed. Unlike previous systems, it applies fuzzy logic for improved accuracy by considering rainfall and wind speed. Sensor errors ranged from 2.14% to 3.19%, with data transmission to ThingSpeak taking 11 seconds (99.94% accuracy) and to a website averaging 15.03 seconds. Fuzzy logic enhanced the system's warning accuracy.

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Publication Details

Journal
Jurnal Ecotipe (Electronic Control Telecommunication Information and Power Engineering)
Published
2025-04-08
DOI
https://doi.org/10.33019/jurnalecotipe.v12i1.4529
Primary Topic
Multimedia Learning Systems
Type
article
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article

Implementation of Fuzzy Logic for Early Warning System for Flood Disaster in Cilacap District

Zaenurohman Zaenurohman, Erna Alimudin, Arif Sumardiono
Jurnal Ecotipe (Electronic Control Telecommunication Information and Power Engineering)
Multimedia Learning Systems
article

Implementation of Fuzzy Logic for Early Warning System for Flood Disaster in Cilacap District

Zaenurohman Zaenurohman, Erna Alimudin, Arif Sumardiono
article en

Abstract

Indonesia's tropical climate and high rainfall frequently lead to unnoticed river overflows, causing significant health and economic losses. A Flood Early Warning System (EWS) using LoRa communication and an Arduino Mega2560 microcontroller was developed, incorporating ultrasonic, DHT11, rain gauge, and anemometer sensors to measure water level, temperature, humidity, rainfall, and wind speed. Unlike previous systems, it applies fuzzy logic for improved accuracy by considering rainfall and wind speed. Sensor errors ranged from 2.14% to 3.19%, with data transmission to ThingSpeak taking 11 seconds (99.94% accuracy) and to a website averaging 15.03 seconds. Fuzzy logic enhanced the system's warning accuracy.

Jurnal Ecotipe (Electronic Control Telecommunication Information and Power Engineering)Vol. 12(1)
Openalex Percentile: Top 89%
Multimedia Learning Systems
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