IoT-Based Decision Support System for Rapid Decision Making in Flood Management in Smart Cities darmawan
Universitas Muhammadiyah Buton
Abstract
This research focuses on the development and implementation of an Internet of Things (IoT)-based Decision Support System (DSS) to address urban flooding, in line with smart city trends that require the integration of intelligent technology. Flooding often occurs due to heavy rainfall and inadequate drainage systems. This system aims to assist policymakers in making rapid and accurate decisions during flood management. It works by integrating IoT sensors to monitor critical environmental parameters in real time, such as water levels, rainfall intensity, and water current speed. Data from these sensors is then sent to a central server via a wireless network. The incoming data is processed using Case-Based Reasoning (CBR), an approach that bases decisions on experience or previous flood cases. The CBR process consists of four main steps: Retrieve: Reuse: Revise: Retain. Through this CBR method, DSS can provide recommendations for relevant and adaptive actions to flood patterns in specific locations, such as suggestions for issuing early warnings, organizing evacuations, or arranging the opening of floodgates.
Keywords: Decision Support System, Internet of Things (IoT), Case Based Reasoning (CBR), Smart City, Flood.
Topic: Technological and Scientific Innovation in Coastal Cities
