<![CDATA[The quality of boiler feedwater is a crucial factor in maintaining the operational reliability of ship machinery systems against the risks of corrosion and scale formation. This research focuses on the design and development of a real-time monitoring system based on the Internet of Things (IoT) to automatically determine water quality. The hardware development utilizes a NodeMCU ESP32 microcontroller that integrates four main sensors: a pH sensor, a DS18B20 temperature sensor, a Total Dissolved Solids (TDS) sensor, and a turbidity sensor. The methodology applied is an experimental systems engineering model, encompassing circuit design, software programming, and the implementation of simple artificial intelligence. The automatic decision-making process in this tool is designed using zero-order Sugeno fuzzy logic with input parameters of turbidity, salinity, and acidity level (pH). The obtained data is transmitted wirelessly to a Firebase database and visualized through a 0.96-inch OLED display. Functional tests on seven fluid characteristics including pure water, hard water, and muddy water show that this prototype can accurately classify water quality into Good, Fair, and Poor categories. The main contribution of this design is the provision of a preventive, efficient, and applicable boiler maintenance solution for the modern shipping industry.]]>
Copyrights © 2026
