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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| Format: | Thesis |
| Language: | English English English |
| Published: |
2022
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| Online Access: | 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 http://eprints.uthm.edu.my/8336/ |
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| Summary: | 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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