基于物联网的粉尘浓度数据采集优化设计  

Optimal Design of Dust Concentration Monitoring Data Collection Based on Internet of Things

作　　者：刘敏[1] LIU Min(College of Electronics and Information Engineering,Xi’an Technological University)

机构地区：[1]西安工业大学电子信息工程学院

出　　处：《化工自动化及仪表》2023年第2期194-198,共5页Control and Instruments in Chemical Industry

摘　　要：针对无线传感器网络节点数据传输的耗能性和物联网数据的海量性特点,提出一种LEACH协议和线性回归模型相结合的PM2.5数据采集优化检测系统。该系统以PM2.5粉尘浓度传感器为检测节点,通过研究基于物联网感知层的数据融合算法,提出将线性回归模型与簇状网络结构相结合,构建系统函数,实现节点间相关参数的传输,减少了网络的总能耗,延长了网络生命周期。仿真结果表明:所提数据融合策略达到了节能高效、优化采集数据的目的。Wireless sensor network is Iot’s important means to get monitoring data. Considering energy consumption in the data transmission from wireless sensor network nodes and the data’s massive nature of the Internet of Things, an optimal monitoring system which combining LEACH protocol and linear regression models for PM2.5 data collection was proposed. The system takes PM2.5 dust concentration sensors as detection nodes. Through studying the data fusion algorithms based on the IoT sensing layer, combining linear regression model with a clustered network structure was proposed to construct a system function that enables relevant parameters transmitted between nodes, reduces total energy consumption of the network and increases the network life cycle. Simulation results show that, the proposed data fusion strategy achieves energy efficiency and optimization of the data collection.

关 键 词：数据采集 PM2.5 物联网 线性回归模型 分簇结构 海量数据传输 节能 网络生命周期 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置] TN919[自动化与计算机技术—控制科学与工程]