Design of Flood Early Detection Based on the Internet of Things and Decision Support System

Flooding is a natural disaster that has a serious impact on humans, the environment, and the economy.To reduce the risk and adverse impacts of flooding, this research aims to design an Internet of Things (IoT) based early detection system integrated with a decision support system.The proposed system uses various types of sensors, such as DHT22 to monitor air temperature and humidity, an Ombrometer to measure rainfall, a Water Flow Sensor to measure water flow, and an Ultrasonic Sensor to detect changes in water level.Data from these sensors will be collected in real time and analyzed to predict potential flooding.In addition, the system will have a user interface that facilitates monitoring and decisionmaking by authorities.The decision support system will use sensor data and weather information to warn decision-makers early of potential flooding and appropriate action recommendations.This research is expected to improve the ability to detect and respond to floods more effectively, thereby assisting in protecting human lives, protecting the environment, and reducing the economic impact of floods.In addition, this research contributes to the development of IoT-based technologies and decision support systems in the context of natural disaster mitigation.