基于物联网的室内环境智能监控大数据挖掘系统

Big Data Mining System of Indoor Ambient Intelligence Monitoring Based on Internet of Things

为了提高室内环境智能监控大数据的采集能力,提出基于物联网的室内环境智能监控大数据挖掘系统。系统采用ZigBee物联网组网技术进行原始数据采样,通过温度、湿度传感器等底层构件进行信息感知和识别;采用多传感节点信息融合方法进行大数据融合,分析不同室内环境下大数据的输出特征;根据峰值测量和相关性特征融合的方法,进行挖掘系统输出程序的加载控制和AD转换设计;建立大数据挖掘系统的网络组网协议,对采集信息进行特征融合和优化挖掘;在嵌入式ARM环境中进行数据挖掘系统的指令传输控制和加载,实现系统的集成硬件设计。实验结果表明,采用该系统进行大数据挖掘,输出稳定性较好,智能性和准确性较高。

In order to improve the intelligent monitoring,the intelligent monitoring big data mining system based on the Internet of Things is proposed.The system adopts ZigBee Internet of Things networking technology to sample the raw data,and conducts information perception and identification through the underlying components such as temperature and humidity sensors.Big data fusion was used to analyze the output characteristics of large data in different indoor environments.Load control and AD transformation design of the output program of the mining system according to the method of peak measurement and correlation features fusion;Establish a network networking protocol for big data mining system to fuse and optimize the collected information.Conduct the command transmission control and load of the data mining system in the embedded ARM environment to realize the integrated hardware design of the system.Experimental results show that the output stability of intelligent monitoring is intelligence and accuracy.