AI in urban planning

Urban planners in Singapore have been facing challenges such as land scarcity in the past. In recent years, climate change and sustainability are constantly brought up with regards to the land use in Singapore. Traditional methods such as manual land surveys and analytic models based on census data...

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Main Author: Low, Ryan Wai Zhun
Other Authors: Wen Bihan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/149036
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1490362023-07-07T17:07:39Z AI in urban planning Low, Ryan Wai Zhun Wen Bihan School of Electrical and Electronic Engineering bihan.wen@ntu.edu.sg Engineering::Electrical and electronic engineering Urban planners in Singapore have been facing challenges such as land scarcity in the past. In recent years, climate change and sustainability are constantly brought up with regards to the land use in Singapore. Traditional methods such as manual land surveys and analytic models based on census data were conducted. However, they are either labour intensive which require a huge amount of time or fail to adjust to the dynamic environment. With the advancement of AI and technology nowadays, urban planners can tap on this potential to revolutionise their methods of planning land use configuration. In this paper, a machine learning based framework for land use configuration is proposed. A list of Point-of-Interests and their relevant information are included in a new and distinctive dataset created. Machine learning model is trained with this dataset to accurately predict and rank candidate locations based on their google ratings. An optimal site is the highest ranked candidate location. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-25T01:13:17Z 2021-05-25T01:13:17Z 2021 Final Year Project (FYP) Low, R. W. Z. (2021). AI in urban planning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149036 https://hdl.handle.net/10356/149036 en A3291-201 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Low, Ryan Wai Zhun
AI in urban planning
description Urban planners in Singapore have been facing challenges such as land scarcity in the past. In recent years, climate change and sustainability are constantly brought up with regards to the land use in Singapore. Traditional methods such as manual land surveys and analytic models based on census data were conducted. However, they are either labour intensive which require a huge amount of time or fail to adjust to the dynamic environment. With the advancement of AI and technology nowadays, urban planners can tap on this potential to revolutionise their methods of planning land use configuration. In this paper, a machine learning based framework for land use configuration is proposed. A list of Point-of-Interests and their relevant information are included in a new and distinctive dataset created. Machine learning model is trained with this dataset to accurately predict and rank candidate locations based on their google ratings. An optimal site is the highest ranked candidate location.
author2 Wen Bihan
author_facet Wen Bihan
Low, Ryan Wai Zhun
format Final Year Project
author Low, Ryan Wai Zhun
author_sort Low, Ryan Wai Zhun
title AI in urban planning
title_short AI in urban planning
title_full AI in urban planning
title_fullStr AI in urban planning
title_full_unstemmed AI in urban planning
title_sort ai in urban planning
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/149036
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