Population density analysis for identification of low-risk airspace for UAV operations

Unmanned Aerial Vehicles (UAVs) have been increasing in popularity rapidly in recent years due to their wide variety of applications. As such, many challenges have surfaced, with one of the most concerning being the safety of the general public due to the increased possibility of UAVs crashing on pe...

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Main Author: Tock, Wenhui
Other Authors: Low Kin Huat
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/159179
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1591792023-03-04T20:14:06Z Population density analysis for identification of low-risk airspace for UAV operations Tock, Wenhui Low Kin Huat School of Mechanical and Aerospace Engineering MKHLOW@ntu.edu.sg Engineering::Aeronautical engineering Unmanned Aerial Vehicles (UAVs) have been increasing in popularity rapidly in recent years due to their wide variety of applications. As such, many challenges have surfaced, with one of the most concerning being the safety of the general public due to the increased possibility of UAVs crashing on people on the ground, resulting in higher fatality risk. Thus, as fatality risk is directly associated with population density, there is a need to study the distribution of population density across various areas in Singapore in order to identify low-risk airspace with lower population density for UAVs to fly over. The objective of this report was to identify low-risk airspace in Singapore that can be used for UAV operations through population density analysis considering consumption amenities available in each area. Preliminary data analysis was first carried out to understand the recent population in each area and the population trend over the past 20 years. Detailed data analysis was then done for two planning areas using the Random Walks Method and Gravity Model to understand the population distribution at unsheltered amenities. This final year project will contribute to the development of risk assessment models assessing fatality risks to people on the ground. The safety of UAV operations can thus be improved by avoiding high-risk areas where the population density is high. Bachelor of Engineering (Aerospace Engineering) 2022-06-11T10:34:44Z 2022-06-11T10:34:44Z 2022 Final Year Project (FYP) Tock, W. (2022). Population density analysis for identification of low-risk airspace for UAV operations. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159179 https://hdl.handle.net/10356/159179 en 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::Aeronautical engineering
spellingShingle Engineering::Aeronautical engineering
Tock, Wenhui
Population density analysis for identification of low-risk airspace for UAV operations
description Unmanned Aerial Vehicles (UAVs) have been increasing in popularity rapidly in recent years due to their wide variety of applications. As such, many challenges have surfaced, with one of the most concerning being the safety of the general public due to the increased possibility of UAVs crashing on people on the ground, resulting in higher fatality risk. Thus, as fatality risk is directly associated with population density, there is a need to study the distribution of population density across various areas in Singapore in order to identify low-risk airspace with lower population density for UAVs to fly over. The objective of this report was to identify low-risk airspace in Singapore that can be used for UAV operations through population density analysis considering consumption amenities available in each area. Preliminary data analysis was first carried out to understand the recent population in each area and the population trend over the past 20 years. Detailed data analysis was then done for two planning areas using the Random Walks Method and Gravity Model to understand the population distribution at unsheltered amenities. This final year project will contribute to the development of risk assessment models assessing fatality risks to people on the ground. The safety of UAV operations can thus be improved by avoiding high-risk areas where the population density is high.
author2 Low Kin Huat
author_facet Low Kin Huat
Tock, Wenhui
format Final Year Project
author Tock, Wenhui
author_sort Tock, Wenhui
title Population density analysis for identification of low-risk airspace for UAV operations
title_short Population density analysis for identification of low-risk airspace for UAV operations
title_full Population density analysis for identification of low-risk airspace for UAV operations
title_fullStr Population density analysis for identification of low-risk airspace for UAV operations
title_full_unstemmed Population density analysis for identification of low-risk airspace for UAV operations
title_sort population density analysis for identification of low-risk airspace for uav operations
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/159179
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