A water environment security monitoring algorithm based on intelligent video surveillance

The rational allocation of water resources has become an important prerequisite for the protection of national economic and social sustainable development as the China economic develops rapidly, therefore establishing water security environment monitoring and evaluation mechanisms is a good way for providing services and solutions for regional environmental management and accident pollution. Considering features of super-large water transmission engineering, water environmental safety level assessment strategy based on intelligent video surveillance is designed. According to features of main water surface and that of moving target, and by using SVM the corresponding water environment security level classification model is designed. The application of sample offline learning methods guaranteed efficiency and accuracy of water quality assessment, and the results of several kernels are also analyzed and verified via tests. This algorithm has been successfully used in the central line project of south-to-north water diversion, and the test result shows that this algorithm is of high robustness and accuracy.