Big data analytics for smart transportation

Abstract

We are living in a world which revolves around data, the amount of data grows exponentially as technology enhances. The amount of data that we have can be used for gaining insights into various aspects of the world to aid us in decision making. In Singapore, we can make use of the data collected from vehicles to help us effectively manage traffic flow. The Smart Transportation Project aims to develop a system to process, visualize and analyze the various types of traffic data available. The previous version of the project performed well and could process raw vehicle data, visualize the traffic conditions on the map, Navigating was possible and it could also display generic road details. However, the map reloads as user navigates through the different timestamps of traffic data, the user interface was not informative and interactive and Bus and pathways data was not yet visualized onto the map. The Main objective of this project was to address the problems that existed in the previous version, Techniques like data slicing, data reframing and data clustering was used to improve the interactivity and visuals of the project, displaying of bus and pathway data was also implemented. The report will further elaborate on how the objectives are achieved by implementing a web application using Django Framework, MySQL Database and MapBoxGL.