Water Environment Monitoring System Based on Neural Networks for Shrimp Cultivation

Nowadays, the water quality control in intensive aquaculture is mostly based on single factor in china. The interactions among water factors are often ignored. In this paper, a water environment monitoring system based on BP neural networks is presented, which uses multiple water factors to evaluate whether the water environment is suitable for shrimp growth. In the paper, the whole architecture of the monitoring system is firstly introduced. Then, a multi-sensor information fusion algorithm based on BP neural networks is described in detail. Finally, some actual tests for the information fusion algorithm are given. The test results show that our monitoring system works well with high accuracy.