A Perception for Smart City Planning using Data Mining

Abstract

The rapid urbanization across the globe necessitates the development of smart cities to enhance the quality of life, optimize resources, and ensure sustainable growth. This research paper presents an analytical model for smart city planning using data mining techniques. By leveraging large datasets, cities can be planned and managed more efficiently. The model integrates various data mining techniques such as clustering, classification, regression, and anomaly detection to analyze and predict urban trends. This paper provides a comprehensive analysis of the model, supplemented by illustrative images to demonstrate its application.