Determining of Public Grievances- A Smart Way of City Management

Abstract: �Data Mining� is a method of exploring huge databases with a view to develop distinct knowledge or information. �Smart city�, it's a city that technologically advances and improves the quality of residents daily lives through analyzing real time data. The above mentioned terms describes an efficient process for determining public grievances based on the data set to analyze and predict the similar grievance nature for a city. The grievance consists of grievance category such as garbage, sewage drains, water supply etc., and is also composed of attributes like �latitude and longitude� of the grievance registered. Utilizing the above mentioned attributes and data, analysis is performed on real data collected for various cities using �Bounding Box� concept and clustering algorithm �K-means Algorithm�. Results of cluster analysis show the comparison between cities and help the city planners to satisfy and fulfil the needs of citizens and make city sustainable.

Keywords: Data Mining, Smart City project, Google Map API, K-means clustering.