Abstract
The increasingly serious water pollution problem makes efficient and information-based water quality monitoring equipment particularly important. To cover the shortcomings of existing water quality monitoring methods, in this paper, a mobile water quality monitoring system was designed based on LoRa communication and USV. In this system, the USV carrying water quality sensors was used as a platform. Firstly, the LoRa network is used to monitor water quality over a large area. Secondly, the unmanned surface vessel controls the position error within ±20 m and the velocity error within ±1 m/s based on the Kalman filter algorithm. Thirdly, the genetic algorithm based on improved crossover operators is used to determine the optimal operational path, which effectively improves the iterative efficiency of the classical genetic algorithm and avoids falling into local convergence. In the actual water surface test, its packet loss probability within a working range of 1.5 km was below 10%, and the USV could accurately navigate according to the preset optimal path. The test results proved that the system has a relatively large working range and high efficiency. This study is of high significance in water pollution prevention and ecological protection.
Highlights
Today, the water quality in coastal and inland lakes is deteriorating under the influence of increasing human social and economic activities
This paper investigates efficient water quality monitoring methods
To cover the deficiencies of the existing water quality monitoring system, a mobile water quality monitoring system has been designed based on LoRa communication and USV in this paper
Summary
The water quality in coastal and inland lakes is deteriorating under the influence of increasing human social and economic activities. The data collection and monitoring of the water area take an important part in the protection and management decision-making of the water ecosystem. In spite of the research achievements, several problems in the field of water quality monitoring still need to be tackled. (i) Monitoring scope: for large natural reserves of hundreds or even thousands of square kilometers, expensive economic costs will be incurred if monitoring and sensing device is arranged. (iii) Daily maintenance of device: a traditional monitoring device needs manual inspection and maintenance one by one, which will cause high human resource costs [2]. To address these issues, this paper investigates efficient water quality monitoring methods
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