Standing water on airport runways may reduce aircraft braking performance and increase the risk of hydroplaning during takeoff and landing. This study developed an IoT-based standing-water monitoring prototype to support preventive maintenance at Sultan Mahmud Badaruddin II International Airport in Palembang. An R&D method was applied. The system integrated JSN-SR04T ultrasonic sensors, GPS, Raspberry Pi, Arduino, and a camera with U-Net image segmentation, all connected to a web dashboard via HTTP. The dataset consisted of 1,200 runway water images divided into training (70%), validation (20%), and testing (10%) sets. Testing showed that the ultrasonic sensor achieved optimal accuracy at water depths above 2 cm, while the camera detected clear water up to 1.5 m and turbid water up to 2 m. User validation with five expert respondents yielded a feasibility score of 91%, categorized as excellent.
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