Data visualization for smart transportation

• Main Author: Neo, Yeow Yang
• Other Authors: Mo Li
• Format: Final Year Project
• Language: English
• Published: 2016
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/69120
• Institution: Nanyang Technological University

Smart transportation has become increasing essential as the population in Singapore continues to grow rapidly. As a developed country, it is vital that our transportation is effective and efficient. With the rapid rise in information technology, transport data is becoming increasing emergent and is projected to grow significantly in the coming years. This make it possible to effectuate the hidden benefits of large amount of available data for smart transportation through the use of a data-centric visualization approach, revealing potential applicable information. Accompanied by appropriate visualization techniques, these data are able to provide organizations with better insights on decision-making through predictive and behavioural analysis which leads to an overall improved performance. However, the challenge lies in the conversion of data into useable information through pattern identifications and deviations of solutions from those patterns. The focus of this project will be on transport data visualization. The project aims to develop interactive applications that employs large amount of data to visualize transportation matters such as traffic conditions, taxi availability and the concentration of vehicles. Two versions of the Application will be developed, one for Windows platform and another on the Web. Both Application will make use of the data provided to visualize data. Users can load their map data and employ the interactive functionalities within the Applications to visualize and make sense of transport data. Some instances of the functions covered in this project are the visualization of heatmap concentration and traffic congestion levels. Equipped with such visualization tools, users will be able to devise better strategies and make informed decisions through precise data analysis.