Sistem Jemuran Otomatis Berbasis Deteksi Visual dan Sensor Hujan dengan ESP32 - Muhammad Rizki Andrian Fitra; Neysa Talitha Jehian; Sybil Auzi; Thania Dealva Arsyad; Hermawan Syahputra (Jurnal Informatika Dan Tekonologi Komputer (JITEK), 2025)
Unpredictable weather in tropical regions often disrupts clothes drying activities, as sudden rain can cause clothes to become wet again. To address this issue, this study developed an automatic clothes drying system based on ESP32-CAM that can detect weather conditions using two main methods: sky image analysis and rain sensors. The system periodically captures sky images using the ESP32-CAM camera, then analyzes the brightness and contrast of the images to determine weather conditions, with brightness thresholds < 100 and contrast > 30 indicating cloudy weather. Data from the rain sensor is used as additional verification to enhance system accuracy. The decision-making logic combines both data sources to determine whether the clothesline should be retracted or left open. Offline image classification results show an accuracy of 93.67%, while direct testing against 10 weather scenarios yields a system accuracy of 100%. With its high performance and adaptive response to weather changes, this system demonstrates significant potential for implementation as an Internet of Things (IoT)-based home automation solution.