Abstract
A smart city can be referred as a city developed and maintained with the help of Information Technology (IT) to improve the quality of life of citizens. Smart city researches and projects are considered as integral part of city modernization. The huge increase in population and resource consumption has created new challenges and difficulties in urbanization process. Using the traditional database, smart city development is trying to understand, how one can achieve the better ‘quality of life’ with various technology solutions. In other words, a smart city can be described as, ‘A technology based solution-centric smart habitats for citizens’. A smart city development focuses on various areas and categories; for example, water consumption, health care, mobility, public safety, education, energy and smart infrastructures. The scope of the project has been restricted to design and development of a data warehouse to support crime analysis using datasets of Chicago city. The project scope includes requirement gathering, collection of datasets, data design, data modelling, data mining, implementation and testing of a data mart for the ‘Crime analysis of Chicago city’. Crime analysis is an organized method of classifying and examining patterns and trends in crime. The main objective of this web application is to educate the citizens about the future crime events, their occurrences, causes, locations and safety procedures. This application helps citizens to gain knowledge from available datasets, generate the patterns and to find safe and livable locations. The datasets are being collected from City of Chicago city data portal website. This website has the crime dataset with records of all the crime events happened from 2001 till present day. This project directs user to get safety alerts about the unsafe passages depending on location, year, time and temperature. The user can enter any custom location address or can select the address from given list of different locations. Citizens can get the predictions of crime rate and crime type within the diameter of 0.8 miles. The outcomes of predictive analysis are accessible in form of charts, bars, graphs and maps so that users can understand the predictions clearly. The web application is developed using PHP, JSP and HTML, whereas MySQL is used as a backend to store the Data mart.