Name
Abstract | ||
|---|---|---|
Water quality sensor networks can be used for monitoring water environment, early warning and prevention of water pollution through accurate collection of water quality information. Effective deployment of the network can improve its monitoring efficiency. After the uniform deployment of the network, the sensor nodes need to be deployed in the key areas reasonably, so as to save the hardware cost and improve the monitoring effect. In this paper, the water area characteristic model is established to get the key monitoring area. Besides, the Gaussian plume model is applied to obtain the impact range of the key monitoring areas. The experimental results show that Qianhai is the key monitoring area, and its impact range is 10.36 m. On this basis, we deploy the sensors using particle swarm optimisation. Simulation results show that key area can be monitored better, whereas other regions can still guarantee a maximum coverage with a total coverage rate of 79.09%. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1002/int.22828 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Keywords | DocType | Volume |
Gaussian plume model, particle swarm optimisation, sensor deployment, water area characteristic model, water quality sensor networks | Journal | 37 |
Issue | ISSN | Citations |
4 | 0884-8173 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qian Sun | 1 | 0 | 0.34 |
| Fengbo Yang | 2 | 0 | 0.34 |
| Xingyun Yu | 3 | 0 | 0.34 |
| Xiaoyi Wang | 4 | 37 | 16.96 |
| Jiping Xu | 5 | 0 | 0.34 |
| Ning Cao | 6 | 0 | 0.34 |
| Huiyan Zhang | 7 | 0 | 0.34 |
| Li Wang | 8 | 0 | 0.68 |
| Jiabin Yu | 9 | 0 | 3.04 |