School of Marxism, Chang'An University, Xi'an 71000, China.
Comput Intell Neurosci. 2022 Jul 21;2022:3543937. doi: 10.1155/2022/3543937. eCollection 2022.
Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country's strategic requirements for water resources and water ecological protection. This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet of Things technology to develop water quality monitoring sensors, so as to realize the construction of low-cost, high-reliability water quality monitoring demonstration applications. First of all, we established the design of the water quality collection terminal, designed the low-power water quality sensor node, supported the Internet of Things protocol and the collection of various water quality parameters, and used networking for data transmission. Secondly, we use the ant colony algorithm-based system clustering model to obtain a cluster map of water quality monitoring tasks in a certain section of the Weihe River Basin. We take the task clustering graph as an example for analysis, optimize the monitoring model through the ant colony algorithm, and obtain the weight of the optimization index. The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance.
以物联网技术为支撑，开发水质监测传感器，实现低成本、高可靠性的水质监测示范应用。首先，建立了水质采集终端设计方案，设计了低功耗水质传感器节点，支持物联网协议和多种水质参数采集，并采用组网进行数据传输。其次，利用基于蚁群算法的系统聚类模型，获取渭河流域某段的水质监测任务聚类图。以任务聚类图为例进行分析，通过蚁群算法对监测模型进行优化，得到优化指标的权重。监测点的调度任务限制权重变大，因此监测任务的发布主要影响监测点的调度任务限制。通过以上工作，设计并实现了一套基于物联网和数据挖掘技术的在线水质监测系统。该系统可为大规模水资源保护和水环境保护提供参考。
