Stevi Sianipar
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IoT-Based ESP32 System for Real-Time Monitoring of Coffee Fermentation Parameters Istas Manalu; Frengki Simatupang; Gerry Wowiling; Stevi Sianipar; Lewi Siagian; Jose Raja
Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i4.757

Abstract

Coffee fermentation is a vital stage in the post-harvest process that significantly influences the sensory quality of coffee beans. Through microbial activity, fermentation breaks down the mucilage attached to the beans and produces volatile compounds that shape the final flavor and aroma. This process not only affects organoleptic qualities but also boosts the coffee’s market value, especially in the specialty coffee segment. Therefore, fermentation is essential for farmers, producers, roasters, and consumers, and it also offers opportunities for innovation and research in coffee processing. This study aims to develop and deploy an Internet of Things (IoT)-based coffee fermentation monitoring system with a visual interface using the Blynk platform. The system monitors key fermentation parameters—pH, temperature, and humidity—in real time, enabling a more measurable and consistent post-harvest process. Coffee fermentation is a crucial post-harvest step that determines coffee quality. As fermentation progresses, it helps decompose the mucilage on the beans and produces volatile compounds that influence flavor. Fermented coffee is expected to increase in value, particularly in the specialty coffee market. This makes it vital for farmers, producers, and consumers. During a 48-hour fermentation test, the system successfully recorded a pH change from 6.64 to 3.99, temperatures between 28.1°C and 28.9°C, and humidity levels decreasing from 94.1% to 90.1%. These data indicate active fermentation, consistent with characteristics of a wine coffee production process. Additionally, the Blynk interface allows users to set target values, select fermentation profiles, and remotely view historical graphs. The system also demonstrated stable connectivity and quick response during testing. While the system performed well, some improvements are needed, such as parameter input validation and the addition of an automatic alarm feature. Overall, the system shows great potential for enhancing the efficiency and consistency of coffee fermentation quality, especially for small- and medium-sized enterprises.