University of Oulu

P. Samarakkody, S. Guruge, D. Samaradeera, E. Jayatunga and P. Porambage, "Enhance Data Collection Process of a UAV-aided Low Power IoT Wireless Sensor Network," 2021 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2021, pp. 1-6, doi: 10.1109/WCNCW49093.2021.9419977

Enhance data collection process of a UAV-aided low power iot wireless sensor network

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Author: Samarakkody, Pasan1; Guruge, Sachith1; Samaradeera, Dulaj1;
Organizations: 1Department of Electrical and Information Engineering, University of Ruhuna, Galle, Sri Lanka
2Centre for Wireless Communications, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-21


Amalgamation of low power IoT devices in Wireless Sensor Networks (WSNs) has enhanced the usage of WSNs as it lessens the requirements of total power consumption. Most such IoT devices comparatively employ short-range radio access technologies such as Bluetooth Low Energy (BLE) to transfer sensor data. When a WSN is situated in a remote region such that neither regular human monitoring is plausible nor Internet coverage is readily available, it requires an alternative method to gather data from sensor nodes. Hence, in this research, an attempt was made to improve the data collection process and monitor the parametric performance of a low power IoT WSN aided by an Unmanned Aerial Vehicle (UAV). The impact of physical parameters related to different sensor node arrangements was investigated to effectively utilize the total flying time of the drone. Subsequently, adjustments were proposed for improvements by referring to previous literature. The Hamiltonian path defined in Graph Theory was applied to reduce the traverse distance of the drone further by tracing the sensor nodes within the grid area systematically. A prototype was implemented using commercially available devices to demonstrate the feasibility and the functionality of the proposed solution. Our results show that the proposed system increases the data collection performance by 23% compared to referenced architecture.

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ISBN: 978-1-7281-9507-0
ISBN Print: 978-1-7281-9508-7
Article number: 9419977
DOI: 10.1109/WCNCW49093.2021.9419977
Host publication: 2021 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2021, 29-29 March 2021, Nanjing, China
Conference: IEEE Wireless Communications and Networking Conference Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
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