The Monitoring and Early Warning System of Water Biological Environment Based on Machine Vision

Abstract

Water contaminated by microorganisms can lead to the outbreak and prevalence of various diseases, which seriously threaten the health of people. In the monitoring of the water biological environment, the traditional methods have low detection sensitivity and low efficiency, so it is urgent to design a water biological monitoring system with low cost and high monitoring efficiency. Machine vision has the advantages of fast speed, appropriate precision, and strong anti-interference ability, which has been greatly developed in recent years. In this paper, the monitoring and early warning system of the water biological environment is built, in which the SVM algorithm is applied to image processing and feature extraction, and each module of the system is designed. Finally, the computational complexity of the system algorithm and the detection accuracy of the system are tested, and the results show that the system has the advantages of low cost, low computational complexity, and high monitoring efficiency, which can provide a reference for water resources protection.