Development of UAVs System Based on Cluster Drones Flight Technology for Water Quality Measurement 


Vol. 43,  No. 2, pp. 371-381, Feb.  2018
10.7840/kics.2018.43.2.371


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  Abstract

In this paper, due to the recent changes in the environment, the development of unmanned aerial systems for measuring water quality is proposed for the purpose of preparing for water pollution, which is rapidly increasing the frequency of algal bloom and red tides. In order to minimize the direct and indirect damages caused by the tides of algal bloom, it analyzed the representative water quality measurement work undertaken by the relevant agencies, and determined that the existing methodology was used to determine the need for a large quantity of cost and time, and derive the need for water quality measurement systems. To test the efficiency of the water quality measurement using cluster drones, a community flight system consisting of one ground control system(GCS) and eight unmanned aerial aircraft were developed and tested. As a result, the water quality measuring system utilizing a number of cluster drones technologies is provided to supplement the existing water quality measurement system.

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  Cite this article

[IEEE Style]

J. Song and S. Heo, "Development of UAVs System Based on Cluster Drones Flight Technology for Water Quality Measurement," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 2, pp. 371-381, 2018. DOI: 10.7840/kics.2018.43.2.371.

[ACM Style]

Ji-hong Song and Sung-phil Heo. 2018. Development of UAVs System Based on Cluster Drones Flight Technology for Water Quality Measurement. The Journal of Korean Institute of Communications and Information Sciences, 43, 2, (2018), 371-381. DOI: 10.7840/kics.2018.43.2.371.

[KICS Style]

Ji-hong Song and Sung-phil Heo, "Development of UAVs System Based on Cluster Drones Flight Technology for Water Quality Measurement," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 2, pp. 371-381, 2. 2018. (https://doi.org/10.7840/kics.2018.43.2.371)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880