基于FPGA和KNN粒子聚类的商场多元监测设计

Multiple Monitoring Design Based on KNN Particle Clustering and FPGA

在无线传感器网络构架下,基于FPGA和KNN粒子聚类算法进行系统控制算法设计,提出一种改进的商场多元安防监测系统设计方案,进行系统硬件层设计、系统软件层设计。功能模块设计中进行了商场环境信息采集模块、火灾自动报警模块、温湿度自动预警模块、烟气报警模块和安全防盗模块设计。软件实现中引入商场火灾、温湿度等信息报警数据融合的KNN粒子聚类算法。算法仿真和系统测试结果表明,该系统对数据融合精度较高,聚类性好,为实现多元安防监测提供准确的数据基础,系统功能健全,实时性好,用户终端界面友好,交互性强,稳定性高,具有非常好的应用价值。

Under the wireless sensor network framework, based on FPGA and KNN particle clustering algorithm for system control algorithm design, puts forward an improved store multiple security monitoring system design scheme. The paper designs the system hardware and software layer. Functional module design finishes the store environment information collection module, automatic fire alarm module, temperature and humidity automatic warning module, smoke alarm module and anti-theft security module. Software implementation is introduced into stores information such as fire, temperature and humidity alarm data fusion KNN particle clustering algorithm. Algorithm simulation and system test results show that the system for data fusion accuracy is higher and clustering＇s performance is better. Accurate data basis was provided for realizing the multiple security monitoring, system function, good real-time, terminal user friendly interface, strong interactivity, high stability, has the very good application value.