Big data analytics for smart transportation

• Main Author: Zhang, Jie
• Other Authors: Li Mo
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: http://hdl.handle.net/10356/70187
• Institution: Nanyang Technological University

Nowadays, big data has been used more and more in gaining insights into various aspects of the world as well as helping with various decision making. Particularly, in cities like Singapore, by utilizing the large amounts of data collected from urban vehicles, it is possible to analyse and manage the urban traffic in a much more effective way. With that as the background, the Smart Transportation project was launched, which aimed to build a smart system for processing, visualizing and analysing traffic data. The previous FYP student that worked on this developed a traffic visualization system that can process raw vehicle data and visualize the traffic conditions on a map. However, this system is not yet quite usable due to three problems. First, it is very slow at loading traffic data for visualization, and sometimes crashes. Second, it only provides a rough view of the traffic conditions but does not provide the functionality to view the details. Third, the way it processes raw vehicle data is not fast enough in the case of real-time data inputs. The focus of this project is on addressing the problems in the previous system. Techniques like data slicing and data clustering are used to improve the data loading speed in visualization. New useful functionalities like viewing traffic details are added to the system. Last but not least, cluster computing technologies is utilized to speed up the data processing. This project achieves faster and smoother data loading in visualization and 8x speedup in data processing.