Big data analytics for smart transportation

In today’s world, many people are heavily relying on public transport to get to their destination. However, these transports may be affected by unforeseen events which causes delay in the travel time for commuters. Through the use of smart card data, data analytics can be applied to this problem to...

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Main Author: Tan, Jenny Ya Ting
Other Authors: Mo Li
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/137959
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1379592020-04-20T09:01:01Z Big data analytics for smart transportation Tan, Jenny Ya Ting Mo Li School of Computer Science and Engineering limo@ntu.edu.sg Engineering::Computer science and engineering In today’s world, many people are heavily relying on public transport to get to their destination. However, these transports may be affected by unforeseen events which causes delay in the travel time for commuters. Through the use of smart card data, data analytics can be applied to this problem to optimize transport routes and frequencies for commuters. In this project, the main objective is to come up with a web-based visualization for users to visualize the routes of alternative buses that commuters can take during rail disruptions. In this report, it will elaborate on how this project is implemented using Python, Django Framework, MySQL database and MapBoxGL to achieve the main objective of this project. Bachelor of Engineering (Computer Science) 2020-04-20T09:01:01Z 2020-04-20T09:01:01Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/137959 en SCSE19-0484 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Tan, Jenny Ya Ting
Big data analytics for smart transportation
description In today’s world, many people are heavily relying on public transport to get to their destination. However, these transports may be affected by unforeseen events which causes delay in the travel time for commuters. Through the use of smart card data, data analytics can be applied to this problem to optimize transport routes and frequencies for commuters. In this project, the main objective is to come up with a web-based visualization for users to visualize the routes of alternative buses that commuters can take during rail disruptions. In this report, it will elaborate on how this project is implemented using Python, Django Framework, MySQL database and MapBoxGL to achieve the main objective of this project.
author2 Mo Li
author_facet Mo Li
Tan, Jenny Ya Ting
format Final Year Project
author Tan, Jenny Ya Ting
author_sort Tan, Jenny Ya Ting
title Big data analytics for smart transportation
title_short Big data analytics for smart transportation
title_full Big data analytics for smart transportation
title_fullStr Big data analytics for smart transportation
title_full_unstemmed Big data analytics for smart transportation
title_sort big data analytics for smart transportation
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/137959
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