Abstract
A smart city is a modern habitat that uses internet of things (IOT) to collect data and manage resources to provide high level of services to people. Information and communication technology (ICT) is a technique to enhance the quality of a smart city. Semantic web and cloud servers are the resources to provide data for smart city management tools. Riyadh is one of the smart cities in Kingdom of Saudi Arabia. Dust storm and floods are the most common hazards in the city. Existing smart city management could not provide an effective solution for the natural hazards. There is a necessity for smart city applications to optimise data and provide an optimum accuracy in output. The objective of the paper is to provide a solution for natural hazards and provide effective management of Riyadh city. A machine learning technique, interior search algorithm is used in the proposed study. It is used in the research for the extraction of knowledge from complex data. The efficiency of proposed method is compared with state of the art algorithms. The proposed method has achieved an accuracy of 87% in the management of natural hazards.
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