학술논문
A Machine Learning Assisted Method for Coverage Optimization in a Network of Mobile Sensors
Document Type
Periodical
Author
Source
IEEE Transactions on Industrial Informatics IEEE Trans. Ind. Inf. Industrial Informatics, IEEE Transactions on. 19(6):7301-7311 Jun, 2023
Subject
Language
ISSN
1551-3203
1941-0050
1941-0050
Abstract
In this work, efficient algorithms are developed to increase the area covered by a network of mobile sensors. The sensors are divided into $k$ sets, and then the proposed algorithms perform iteratively to increase the area covered by at least $k$ sensors as much as possible. Since the performance of the algorithms highly depends on the initial positions of sensors, we use the $K$-means clustering technique for partitioning the sensors into $k$ sets. Simulation results confirm the effectiveness of the proposed algorithms. They also show that using the $K$-means clustering technique improves the performance of the algorithms in terms of energy consumption, covered area, and convergence time.