摘要
采用物联网(IoT)体系结构,利用虚拟仪器(LabVIEW)技术优势,选用ZigBee技术系统级芯片CC2530,设计出低功耗、低成本、组网灵活的无线火灾监测系统。重点对系统感知层的网络拓扑结构的灵活性、低功耗传感器选型及其低功耗供电模式、节点硬件模块进行设计。采用BP神经网络模型对三种火灾特征监测信号进行数据融合,提高系统火灾报警的准确度,减少数据传输流量、降低节点能耗。
The wireless fire monitoring system with flexible tion and at low cost. Its processor architecture is internet of network mode is designed at low power consump-（IoT）. The design applies the WSN technol-ogy and Virtual Instrument technology LabVIEW. The system on chip （SoC） CC2530 based on ZigBee is as MCU. The emphasis of the design is on the network topology flexibility , and the low power consumption on choice of sensor and its power supply mode. Its hardware structure is modularized. BP Neural network is ap-plied to realize three fire characteristic monitoring signal data fusion . As a result, the accuracy of fire alarm system is improved, the data transmission flow and the node energy consumption are reduced.
出处
《安阳工学院学报》
2013年第2期50-53,共4页
Journal of Anyang Institute of Technology
基金
江苏师范大学科研基金资助项目(编号:11XLB08)
关键词
物联网
无线传感器网络
火灾监测
低功耗
神经网络
internet of things
wireless sensor network
fire monitoring
low power consumption
neural network
