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A Tensor Completion-Based Selection Method of a Single Data Collection Point for Multiple Shelters in a UAV Enabled Disaster Recovery Network

Authors:
Azusa Danjo
Shinsuke Hara
Takahiro Matsuda
Fumie Ono

Keywords: Unmanned Aerial Vehicle; Received Signal Strength; Tensor Completion.

Abstract:
In this paper, we propose a method for selecting a single data collection point for an Unmanned Aerial Vehicle (UAV)-enabled disaster recovery network where UAVs need to collect messages from refugees while hovering above multiple shelters. Just by sensing the Received Signal Strengths (RSSs) for the wireless signals transmitted from multiple shelters at fewer randomly-selected points in the three-dimensional (3D) region above a disaster-hit area, through a tensor completion, the proposed method reconstructs full RSS maps for the multiple shelters in the entire 3D region, and selects a single data collection point using the reconstructed RSS maps where UAVs can collect messages from them more quickly and more energy-efficiently. The experimental results reveal that by sensing RSSs in 25% of a 3D region, the proposed method can collect messages from three transmitters using a shorter route of UAV in a shorter message collection time.

Pages: 7 to 12

Copyright: Copyright (c) IARIA, 2020

Publication date: February 23, 2020

Published in: conference

ISSN: 2308-4480

ISBN: 978-1-61208-769-6

Location: Lisbon, Portugal

Dates: from February 23, 2020 to February 27, 2020