摘要
智慧校园内部电气设备种类与数量较多,实际运行中难免出现异常状态。因此,研究基于物联网技术的智慧校园电气设备远程监控方法。在智慧校园中部署一个由感知层、网络层、应用层组成的物联网架构,采集电气设备运行数据,并进行去噪与归一化等处理。构建径向基函数(Radical Basis Function,RBF)模型实时识别异常运行数据,实现智慧校园电气设备的远程监控。实验结果表明,设计方法下智慧校园电气设备远程监控结果的误报率为0.47%,决定系数为0.953 1,监控性能优越。
There are many types and quantities of electrical equipment inside the smart campus,and abnormal states are inevitable during actual operation.Therefore research on remote monitoring methods for electrical equipment in smart campuses based on Internet of Things technology.Deploy an Internet of Things architecture consisting of a perception layer,a network layer,and an application layer in a smart campus,collect operational data of electrical equipment,and perform denoising and normalization processing.Build an Radical Basis Function(RBF)model to real-time identify abnormal operating data and achieve remote monitoring of electrical equipment in smart campuses.The experimental results show that the false alarm rate of remote monitoring of electrical equipment in smart campus under the design method is 0.47%,with a determination coefficient of 0.9531,indicating superior monitoring performance.
作者
吴良淞
WU Liangsong(Huangyan District First Vocational and Technical School,Taizhou,Zhejiang 318020,China)
出处
《智能物联技术》
2025年第4期38-41,共4页
Technology of Io T& AI
关键词
物联网技术
智慧校园
电气设备
远程监控
监控方法
Internet of Things technology
smart campus
electrical equipment
remote monitoring
monitoring methods
