Rancang Bangun Prototype Sistem Monitoring Ketinggian Air Sungai Berbasis Mikrokontroler ESP32 dan Telegram sebagai Upaya Deteksi Banjir Secara Dini (Mitigasi Banjir)

Flooding is a common disaster caused by high rainfall and inadequate
drainage systems. This study developed a water level monitoring system based on
the Internet of Things (IoT) using the ESP32 microcontroller and HC-SR04
ultrasonic sensor, integrated with Telegram and a website for real-time monitoring.
The Fuzzy Sugeno method is applied to classify water levels into three categories:
Safe, Alert, and Danger. Water level data is transmitted to a server via an API and
displayed on a website, as well as sent as notifications through Telegram. Testing
showed that the sensor achieved 99% accuracy, with fast and reliable notifications
during critical conditions. The results demonstrate that the system is effective for
early flood warning. Future development may include AI-based prediction to
improve early detection accuracy.