Utilizing SECONDO moving objects database technology to simulate MRT usage in Singapore

• 主要作者: Choo, Wei Liang
• 其他作者: Ho Shen-Shyang
• 格式: Final Year Project
• 語言: English
• 出版: 2015
• 主題: DRNTU::Engineering::Computer science and engineering::Information systems::Database management; DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
• 在線閱讀: http://hdl.handle.net/10356/62845
• 機構: Nanyang Technological University

In these days, there are different kinds of databases such as relational databases and temporal databases. Each type of databases is specially implemented to suit the needs of a system. For example, a grocery shop does not require moving objects database to store its transaction of the sales. Thus, a relational database is more suitable. Retrieving of trains that will keep track of coordinates, movements and directions from one place to another are not possible in a relational database model and therefore, moving objects database is required to support these tasks. Moving objects database provides a way to store information where location and time are important for the users. The objective of this project is to demonstrate how to make use of SECONDO, a moving objects database platform to simulate the MRT system in Singapore. In order to use SECONDO, it is necessary to understand some of the key features of the system such as data types and operators. Furthermore, a database design has been drafted out in order to visualise the key elements for the implementation. The implementation will be incorporated with the data from the MRT system. Queries will then be performed to show the results. On top of that, a comparison was made upon the query with and without the aid of an optimizer, a feature provided by SECONDO. The results have shown higher efficiency and better performance as the query time has been improved with the use of an optimizer. It is recommended to setup using a Linux environment as compared to Windows environment due to incompatibly and installation issues. Furthermore, using indexing to do querying in large amount of data may prove to be more efficient.