Real Time Smart Trash Bins Monitoring System Using Fuzzy Logic Method in Kuripan Village

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Published Feb 29, 2024
DOI https://doi.org/10.20895/inista.v6i1.1392

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Dwi Septiyan Nugroho
Program Studi Informatika, Fakultas Matematika dan Ilmu Komputer, Universitas Nahdlatul Ulama AL Ghazali, Cilacap
Safiq Rosad
Informatics, Faculty of Mathematics and Computer Science, University of Nahdlatul Ulama Al Ghazali
Ninik Agustin
Informatics, Faculty of Mathematics and Computer Science, University of Nahdlatul Ulama Al Ghazali

Abstract

The rise of electronic technology has transformed people's lifestyles, and they now want convenience, automation, and flexibility, including when it comes to keeping the environment clean by disposing of rubbish where it belongs. However, despite the importance of this issue, awareness of the need to dispose of waste in its proper place remains low. Additionally, garbage bin supervision in Kuripan Village is still manual, exacerbating the problem of waste accumulation caused by the increasing population. To address this issue, we developed an IoT-based system that utilizes the Fuzzy Logic method. This mathematical approach enables the modeling of uncertainty in data processing. The system allows for real-time monitoring of the garbage load level, notifying staff when action is required. The Fuzzy Logic method is then used to determine the appropriate action based on the garbage load level and the last cleaning time. This research involves developing a prototype that uses NodeMCU ESP8266, HC-SR04 ultrasonic sensor, and LCD for data monitoring. The sensor testing demonstrated an accuracy of approximately 96.7%. The system includes an application interface with a login page, main dashboard, volume dashboard, and time dashboard.


 

Article Details

How to Cite
Nugroho, D., Rosad, S., & Agustin, N. (2024). Real Time Smart Trash Bins Monitoring System Using Fuzzy Logic Method in Kuripan Village. Journal of Informatics Information System Software Engineering and Applications (INISTA), 6(1), 70-79. https://doi.org/10.20895/inista.v6i1.1392
Issue
Vol 6 No 1 (2023): November 2023
Section
Centive 2023
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