Research on Sewage Monitoring and Water Quality Prediction Based on Wireless Sensors and Support Vector Machines

Abstract

Water resource protection has an important impact on ecosystem security and human survival. Therefore, water quality testing and early warning of the sewage status are getting more and more attention. In order to solve the problems of information transmission delay and insufficient water quality prediction in current water quality monitoring, this paper proposes a wireless sensor-based dynamic water quality monitoring and prediction technology. Firstly, this paper uses the wireless sensor technology and ZigBee protocol to establish a sewage monitoring model and real-time dynamic monitoring of total nitrogen, total phosphorus, ammonia nitrogen, and other indicators of the water quality of the basin. Secondly, on the basis of wireless monitoring, a support vector algorithm is used to construct a water quality prediction model to make a reasonable prediction of the water quality of the watershed. Finally, the actual test results show that the technology can automatically and real-timely monitor the water quality of the watershed to meet the requirements of water quality monitoring in practical applications.

Design and implementation of a Li River water quality monitoring and analysis system based on outlier data analysis

“…To attain water quality outlier data analysis and pollution early warning, an ontology modeling and rule generation method [44] has been proposed. While several applicable methods [34][35][36][37][38][39][40][41][42][43][44] have been designed for water quality data analysis, integrating these methods into an online analysis system can yield enhanced analysis results.…”

“…Additionally, a water quality monitoring system (WQMS) and water quality analysis algorithm [ 42 ] have been designed and the feasibility of the design scheme has been verified. Furthermore, a support vector algorithm [ 43 ] has been employed to con-struct a water quality model for reasonable analysis and prediction based on wireless monitoring. To attain water quality outlier data analysis and pollution early warning, an ontology modeling and rule generation method [ 44 ] has been proposed.…”

Advances in Machine Learning for Sensing and Condition Monitoring

“…A wireless sensor system was developed by Liu et al [41] to monitor the water quality in real time. The system can handle the problem of delay of data transmission well with robust comparability for water quality forecasting.…”

Remote Sensing–Based Urban Green Space Detection Using Marine Predators Algorithm Optimized Machine Learning Approach

“…Introduced by Vapnik [40], support vector machines (SVM) have gained attentions of the academic community and have become a preeminent pattern recognition approach [55,[80][81][82][83][84][85][86][87][88][89][90]. Given a data sample set S drawn from a data universe X U , a hidden target function f: X ⟶ 0, 1 { }, we first create a labeled training dataset D, where D � (x, y)|x ∈ S and y � f(x) .…”