Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN

Unmanned aerial vehicles (UAV) have enormous potential in enabling new applications in various areas, ranging from communication, military, security, to traffic-monitoring applications. In the context of the highly distributed and vast nature of Internet of Things (IoT) network, UAV could work as Ae...

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Main Author: Ibrahim, Nurul Saliha Amani
Format: Thesis
Language:English
English
English
Published: 2022
Subjects:
Online Access:http://eprints.uthm.edu.my/8336/
http://eprints.uthm.edu.my/8336/1/24p%20NURUL%20SALIHA%20AMANI%20IBRAHIM.pdf
http://eprints.uthm.edu.my/8336/2/NURUL%20SALIHA%20AMANI%20IBRAHIM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/8336/3/NURUL%20SALIHA%20AMANI%20IBRAHIM%20WATERMARK.pdf
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author Ibrahim, Nurul Saliha Amani
author_facet Ibrahim, Nurul Saliha Amani
author_sort Ibrahim, Nurul Saliha Amani
building UTHM Institutional Repository
collection Online Access
description Unmanned aerial vehicles (UAV) have enormous potential in enabling new applications in various areas, ranging from communication, military, security, to traffic-monitoring applications. In the context of the highly distributed and vast nature of Internet of Things (IoT) network, UAV could work as Aerial Gateway (AG) for communications among low-powered and distributed ground IoT devices (ID). This research focused on the path planning and deployment system that can improve decision making thus ensuring resource-efficient UAV mission assignment in utilizing energy during the process of serving ground ID. Due to finite resource, multiple issues need to be considered in designing such system, including AG flight time, coverage radius and the achievable data rate of the ground-to-air system, thus an Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. EECPP consist of two algorithms which is Stop Point Prediction Algorithm using K-Means, which finding the stop point for the AG after grouping the IDs into clusters, and Path Planning Algorithm using Particle Swarm Optimization which connect all of the stop point in shortest route. The result shows that EECPP outperform Close Enough Traveling Salesman Problem (CETSP) by 19.99% in terms of total flight distance. In comparison to Energy-Efficient Path Planning (E2PP), EECPP lowered energy consumption by average of 56.15%. With efficient path planning along with mobile nature of AG, enabled it to hover at each stop points thus making it ideal to be used in remote areas where fixed base station is not accessible, crowded areas with high demand, and in emergency situations.
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format Thesis
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institution Universiti Tun Hussein Onn Malaysia
institution_category Local University
language English
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last_indexed 2025-11-15T20:25:03Z
publishDate 2022
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spelling uthm-83362023-02-15T07:10:56Z http://eprints.uthm.edu.my/8336/ Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN Ibrahim, Nurul Saliha Amani T Technology (General) Unmanned aerial vehicles (UAV) have enormous potential in enabling new applications in various areas, ranging from communication, military, security, to traffic-monitoring applications. In the context of the highly distributed and vast nature of Internet of Things (IoT) network, UAV could work as Aerial Gateway (AG) for communications among low-powered and distributed ground IoT devices (ID). This research focused on the path planning and deployment system that can improve decision making thus ensuring resource-efficient UAV mission assignment in utilizing energy during the process of serving ground ID. Due to finite resource, multiple issues need to be considered in designing such system, including AG flight time, coverage radius and the achievable data rate of the ground-to-air system, thus an Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. EECPP consist of two algorithms which is Stop Point Prediction Algorithm using K-Means, which finding the stop point for the AG after grouping the IDs into clusters, and Path Planning Algorithm using Particle Swarm Optimization which connect all of the stop point in shortest route. The result shows that EECPP outperform Close Enough Traveling Salesman Problem (CETSP) by 19.99% in terms of total flight distance. In comparison to Energy-Efficient Path Planning (E2PP), EECPP lowered energy consumption by average of 56.15%. With efficient path planning along with mobile nature of AG, enabled it to hover at each stop points thus making it ideal to be used in remote areas where fixed base station is not accessible, crowded areas with high demand, and in emergency situations. 2022-06 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/8336/1/24p%20NURUL%20SALIHA%20AMANI%20IBRAHIM.pdf text en http://eprints.uthm.edu.my/8336/2/NURUL%20SALIHA%20AMANI%20IBRAHIM%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/8336/3/NURUL%20SALIHA%20AMANI%20IBRAHIM%20WATERMARK.pdf Ibrahim, Nurul Saliha Amani (2022) Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN. Masters thesis, Universiti Tun Hussein Onn Malaysia.
spellingShingle T Technology (General)
Ibrahim, Nurul Saliha Amani
Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title_full Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title_fullStr Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title_full_unstemmed Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title_short Resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in LoRaWAN
title_sort resource-efficient coverage path planning for unmanned aerial vehicle based aerial gateway in lorawan
topic T Technology (General)
url http://eprints.uthm.edu.my/8336/
http://eprints.uthm.edu.my/8336/1/24p%20NURUL%20SALIHA%20AMANI%20IBRAHIM.pdf
http://eprints.uthm.edu.my/8336/2/NURUL%20SALIHA%20AMANI%20IBRAHIM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/8336/3/NURUL%20SALIHA%20AMANI%20IBRAHIM%20WATERMARK.pdf