针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关...针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关键部位部署无源温度传感器,利用反向散射通信技术实现低功耗数据传输,并借助5G网络将数据传输至边缘服务器处理。随后,采用基于Transformer的异常检测模型,通过多头注意力机制有效捕捉温度数据中的时序特征,结合最大池化操作实现对异常温度的准确识别与预警。实验结果表明,该方案在高电磁干扰环境下的传输成功率达到99.0%,在温度异常检测任务中的精度、召回率和F1值分别为98.7%、97.5%和96.9%,显著优于LSTM和GRU等传统时序模型。研究成果验证了所提方法在复杂高压场景下的适用性和稳定性,可为后续在更高电压等级的特高压设备中推广应用奠定技术基础。展开更多
为了有效地实时监测肉鸡生产过程中的环境因子,提高肉鸡健康养殖水平,本文将传感器技术与窄带物联网(Narrow Band Internet of Things,NB-IoT)技术结合,设计并实现一种肉鸡养殖环境监测系统,使用无线传感器实时监测肉鸡养殖环境中的温...为了有效地实时监测肉鸡生产过程中的环境因子,提高肉鸡健康养殖水平,本文将传感器技术与窄带物联网(Narrow Band Internet of Things,NB-IoT)技术结合,设计并实现一种肉鸡养殖环境监测系统,使用无线传感器实时监测肉鸡养殖环境中的温度、湿度、光照、NH 3等环境因子,采用B/S(浏览器/服务器)模式,运用NB-IoT技术将信息传输至云端服务器。结果表明:通过该方法可实现环境数据查询、绘制环境变化曲线、远程向终端设备下发控制命令等功能。该系统具有低功耗、低成本的优势,操作简便、性能稳定,为养殖户的决策分析提供了有效信息和科学依据。展开更多
Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems...Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.展开更多
文摘针对当前换流站一次设备温度监测中非接触式红外测温存在成本高、准确率低、时效性差等问题,提出一种面向高压场景的温度监控方案。该方案结合5G无源物联网(Passive Internet of Things,P-IoT)技术与Transformer模型。通过在高压设备关键部位部署无源温度传感器,利用反向散射通信技术实现低功耗数据传输,并借助5G网络将数据传输至边缘服务器处理。随后,采用基于Transformer的异常检测模型,通过多头注意力机制有效捕捉温度数据中的时序特征,结合最大池化操作实现对异常温度的准确识别与预警。实验结果表明,该方案在高电磁干扰环境下的传输成功率达到99.0%,在温度异常检测任务中的精度、召回率和F1值分别为98.7%、97.5%和96.9%,显著优于LSTM和GRU等传统时序模型。研究成果验证了所提方法在复杂高压场景下的适用性和稳定性,可为后续在更高电压等级的特高压设备中推广应用奠定技术基础。
文摘为了有效地实时监测肉鸡生产过程中的环境因子,提高肉鸡健康养殖水平,本文将传感器技术与窄带物联网(Narrow Band Internet of Things,NB-IoT)技术结合,设计并实现一种肉鸡养殖环境监测系统,使用无线传感器实时监测肉鸡养殖环境中的温度、湿度、光照、NH 3等环境因子,采用B/S(浏览器/服务器)模式,运用NB-IoT技术将信息传输至云端服务器。结果表明:通过该方法可实现环境数据查询、绘制环境变化曲线、远程向终端设备下发控制命令等功能。该系统具有低功耗、低成本的优势,操作简便、性能稳定,为养殖户的决策分析提供了有效信息和科学依据。
基金supported by the National Natural Science Foundation of China(61571149,62001139)the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Natural Science Foundation of Heilongjiang Province(LH2020F0178).
文摘Fog computing has emerged as an important technology which can improve the performance of computation-intensive and latency-critical communication networks.Nevertheless,the fog computing Internet-of-Things(IoT)systems are susceptible to malicious eavesdropping attacks during the information transmission,and this issue has not been adequately addressed.In this paper,we propose a physical-layer secure fog computing IoT system model,which is able to improve the physical layer security of fog computing IoT networks against the malicious eavesdropping of multiple eavesdroppers.The secrecy rate of the proposed model is analyzed,and the quantum galaxy–based search algorithm(QGSA)is proposed to solve the hybrid task scheduling and resource management problem of the network.The computational complexity and convergence of the proposed algorithm are analyzed.Simulation results validate the efficiency of the proposed model and reveal the influence of various environmental parameters on fog computing IoT networks.Moreover,the simulation results demonstrate that the proposed hybrid task scheduling and resource management scheme can effectively enhance secrecy performance across different communication scenarios.
