A UAV Path Planning Method Using Polynomial Regression for Remote Sensor Data Collection

Koo, Kwang Min; Lee, Kyung Rak; Cho, Sung Ryung; Joe, Inwhee

doi:10.1007/978-981-13-9341-9_74

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A UAV Path Planning Method Using Polynomial Regression for Remote Sensor Data Collection

Koo, Kwang Min;
Lee, Kyung Rak;
Cho, Sung Ryung;
Joe, Inwhee

Citations

SCOPUS

2

초록

The use of Unmanned Aerial Vehicle (UAV) has been increasingly diverse. In Wireless Sensor Networks (WSNs), UAVs are used for sensor data collection. However, the path planning for the UAV is not practical for a large number of sensors, and is not effective for the battery consumption. In this paper, we propose the UAV path planning for data collection in WSNs using Polynomial Regression. With this algorithm, the UAV is able to save the battery and the mission time. ? 2020, Springer Nature Singapore Pte Ltd.

키워드

Machine learning; Path planning; Sensor data collection; UAV; Antennas; Data acquisition; Learning systems; Secondary batteries; Ubiquitous computing; Unmanned aerial vehicles (UAV); Wireless sensor networks; Battery consumption; Data collection; Path planning method; Polynomial regression; Remote sensors; Sensor data collections; Wireless sensor network (WSNs); Motion planning

제목: A UAV Path Planning Method Using Polynomial Regression for Remote Sensor Data Collection

저자: Koo, Kwang Min; Lee, Kyung Rak; Cho, Sung Ryung; Joe, Inwhee

DOI: 10.1007/978-981-13-9341-9_74

발행일: 2020-00

유형: Conference Paper

저널명: Lecture Notes in Electrical Engineering

권: 536 LNEE

페이지: 428 ~ 433