<![CDATA[Floods are a natural phenomenon that occurs when water from rivers, lakes, or seas exceeds its boundaries and inundates surrounding areas, posing threats to humans and animals and causing environmental and infrastructure damage. This study aims to develop an effective early flood detection tool for river areas utilizing IoT technology. The research methodology begins with identifying needs through problem formulation and a literature review on the latest flood detection technologies and the application of IoT in environmental monitoring systems. The designed system involves integrating sensors to monitor flood parameters such as water level and rainfall, with data transmitted in real-time to an IoT-based monitoring center. Development includes designing data analysis algorithms and developing hardware (resistive sensors, NodeMCU) and Android software. Implementation involves installing sensors at strategic locations and testing the system to validate the accuracy and performance of early warnings. System response evaluation is conducted through flood simulations and real conditions, with results disseminated to authorities and the public. Using river coastal models in the simulation system facilitates understanding of field conditions and serves as an educational tool to raise public awareness. On September 17-20, 2023, testing was conducted on the early flood detection simulation tool and the river flow model using the IoT system. Test results indicated that water levels at all locations had a minimum value of 0 cm and a maximum of 10.73 cm on September 18, 2023. Location 4 consistently showed the presence of flooding. This data integration provides a strong basis for authorities in flood disaster planning and management, enabling a faster and more effective response to detected conditions.]]>
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