Fuzzy Logic-Based Decision Support System in Environmental Monitoring of IoT Hydroponic Melon Cultivation
Year: 2026
Type: conference-paper
Abstract: Melon cultivation in hydroponic systems faces challenges due to fluctuating environmental conditions, which can impact crop quality and yield. Conventional monitoring of these conditions is often inefficient, and raw sensor data is difficult for farmers to interpret for rapid decision-making. To address these challenges, this study proposes a mobile-based decision support system for environmental monitoring in hydroponic melon cultivation using Internet of Things (IoT) technology and fuzzy logic inference. The system collects realtime data from pH, temperature, and Total Dissolved Solids (TDS) sensors and sends it to a Firebase Realtime Database. A fuzzy Sugeno inference system is applied to analyze sensor data and classify environmental conditions as either normal or abnormal. The results are visualized in a mobile application built using Flutter, which also provides automated alerts to users. Experimental results show that the system is highly effective in detecting critical changes in growing conditions with an overall accuracy of 99.47%, enabling farmers to take timely action. This research contributes to the advancement of smart agriculture technologies that support precision farming and sustainability.
Institution: Politeknik Elektronika Negeri Surabaya
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7214959152