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Arya Prabudi Jaya Priana
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Social Sciences

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Prediction of flood depth detection system from rainfall with normal, alert and hazard levels based on fuzzy logic Arya Prabudi Jaya Priana; Itqon Madani; Vanya Amanda Lovely; Fiqri NurFadillah; Muhammad Danang Mukti Darmawan; Nanda Octavia
Journal of Applied Science, Technology & Humanities | JASTH Vol. 1 No. 3 (2024): June 2024
Publisher : Batrisya Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62535/ba8ygx44

Abstract

Floods are natural calamities that frequently transpire and are of primary concern for governmental entities due to their potential for significant losses and casualties. Heavy rainfall and overflowing water stand as the primary triggers for flooding. Many communities lack adequate knowledge to forecast floods, thus necessitating technological interventions for early water depth detection and issuing flood warnings. This study devised a water depth detection system based on fuzzy logic using Arduino as a microcontroller. The system employs ultrasonic sensors for water level detection and a Tipping Bucket for precipitation measurement. Its primary objective is to establish a system capable of issuing early flood warnings through alarms. The outcome of this research entails the implementation of an Arduino Uno-based flood detection system that aids users in monitoring water levels and anticipating floods. Safety considerations are also addressed by incorporating fuzzy logic technology to forecast flood potential based on water level and rainfall data. The utilization of fuzzy logic enables the system to navigate uncertainties and ambiguities in data, thus furnishing more precise and dependable early warnings. Consequently, the findings of this study serve as a groundwork for the advancement of more sophisticated and efficient flood detection systems in the future.  
Co-Authors Fiqri NurFadillah Itqon Madani Muhammad Danang Mukti Darmawan Nanda Octavia Vanya Amanda Lovely