An Empirical Data Analytics and Visualization for UBER Services: A Data Analysis Based Web Search Engine
K. Muthamil Sudar, P. Nagaraj, V. Muneeswaran, S. Kavya Jeevana Swetha, K. Madhuri Nikhila, R Venkatesh
Abstract
Uber Data using R programming, we can predict the fare, reduce timing and choose locations based on the heat map. We are creating a website for UBER DATA. Effective taxi dispatching will allow each driver and passenger to spend less time looking for each other. The model is used to forecast demand at various locations throughout the city. In an urban area of any metropolitan city or normal city, people are unable to drive or are most not likely to take their vehicles due to rides. All the people are most likely to take buses, subwaysor taxis. The three modes of transportation are important but have different features. The main difference among all these is fare (way to pay). So, Uber is very popular nowadays. The main aim of this project is that we are creating a website of Uber data so, all the people who are willing to take uber taxis can easily find the data which is on their mobile itself.