SMART CITY RANKING BASED ON BIG DATA

Abstract

The smart urbanization is growing in international urban planning for the last decade. The smart city expresses to combine information and communication technology that defines smart living. A smart city has an infrastructure to provide life quality, a safe and clean environment to its citizens by smart technology. These days people want to live a smart life. So, the urban planner/ researcher is evolving “smart city models” based on the following six dimensions, “environment,” “economy,” “people,” “governance,” “mobility,” and “living.” This model was developed based on “American” and “European” cities. “Make in India” Smart City is a scheme taken by the “Government of India” in 2014 to encourage the multi-national, among national companies, to help in making in Indian smart city. After the start of this program in India would emerge as the top focus in the world for foreign direct investment to make smart city projects. The major objective behind the start is to focus on development creation and smart skill enhancement in the sector of smart city development to living better. The start of Indian smart city also aims to achieve high-quality benchmarks combined with the lowest effect on the environment. The smart city hopes to attract technical as well as a capital investment in India. Smart Cities India is going to grow into the most populated country. The growing population will be transferred to the top-level by cities of India. It will be challenging to cope up with the ever-increasing population in cities with the presently available urban area. So, the vision Prime Minister Narendra Modi is going towards developing more smart v cities, so the plan is to build 100 smart cities has started. The problem of ranking smart cities with the “Indian Smart City Model” is arising. Big data is a solution to manage the massive volume of both structured and unstructured data. The processing of an extensive data set with verity and volume is not possible on traditional software of database and techniques. The generation of data is too large and frequently changes, so the database is becoming too heavy to analyze the information from traditional databases. The objective starts with making a model for Indian smart city with the dimensions and indicators, according to India. This thesis proposed an India Smart City Model with the Eight Dimensions “Demographics Profile,” “Economic Profile,” “Infrastructure Profile,” “E-Governance & computerization,” “Finance,” “Environmental,” “Progress Track,” “Security,” and 80 indicators. These Dimensions and indicators based on the Indian smart city. The present smart city models are based on the European and American smart city indicators. The Indian smart city ranking is now calculating based on eight dimensions and eighty indicators. The Ranking decisions are made on multiple criteria-based problems solved using the “distance-based algorithm (DBA)” to rank the Indian “Smart City.” The algorithm calculates the optimal value solution based on the distance to make an optimal ranking solution for the Smart Indian cities. The multiple indicators having different units and values, the DBA algorithm standardizes all indicators so that the optimal value of ranking can be provided. vi The second algorithm, “Taxicab Distance-Based Approach (TDBA),” is proposed to rank the “Indian smart city.” The TDBA finds the optimal solution on the bases of “Indian smart city” indicators multiple values. The approach calculates the optimal distance solution using taxicab distance to find the best result. The result is showing the ranking of Indian Smart City based on the proposed “Indian Smart City Model,” having eight dimensions and eighty indicators using the algorithms defined in DBA and TDBA. The individual ranking of each dimension for every city is done so that the growth of development can be visualized. This information used for evaluation of city rank using the DBA and TDBA approaches. DBA and TDBA is a mathematical tool that has been used to aggregate and convert data into a standard form that is used to rank “Indian smart cities.” The result clarifies cities' vision and creates a blueprint of the cities that can be useful in the near future.