使用物联网云计算中间件简化智能人群监控
Alexandros Gazis1, Eleftheria Katsiri1,2
1Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, 67100 Xanthi, Greece.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
本研究介绍了一种新的低功耗中间件,用于分析室内无线传感器网络 (WSN) 数据. 它有效地跟踪游客和监控占用使用负担得起的设备,证明有效的历史遗址和博物馆.
科学领域:
- 计算机科学 计算机科学
- 无处不在的计算无处不在的计算
- 网络工程 网络工程
背景情况:
- 博物馆和历史建筑等室内环境需要高效的监控系统来跟踪访客和安全.
- 现有的解决方案通常依赖于资源密集型硬件或复杂的AI技术,限制它们在预算有限或低功耗场景中的适用性.
研究的目的:
- 引入一种新的,具有成本效益的中间件,用于使用低功耗计算设备分析无线传感器网络 (WSN) 数据.
- 为了证明中间件在访问者跟踪,占用监控和室内环境中作为疏散辅助工具的能力.
- 要突出系统的容错性和分布式性质,以便可靠的数据分析.
主要方法:
- 利用低功耗的计算设备 (例如,树派) 来进行数据分析.
- 实现了一个基本的MapReduce算法,用于数据收集和跨节点的分布.
- 采用RFID传感器来收集参观者章数据,并使用微型计算机进行本地存储.
- 在分布式系统中集成了一个领导者选举算法,以实现故障容忍.
主要成果:
- 中间软件成功收集和分析了WSN数据,展示了访问者跟踪和占用监控能力.
- 性能指标验证了系统的可行性,与资源密集型方法相匹配,尽管使用更简单的硬件.
- 使用预算友好型设备的耐故障,分布式设置在真实世界的历史建筑中证明了其有效性.
- 该系统在室内监控应用中显示出快速原型设计和准确验证发现的前景.
结论:
- 开发的中间件为使用低功耗设备进行室内监控提供了创新,耐故障和分布式解决方案.
- 它为资源密集的系统提供了具有成本效益的替代方案,用于访问者跟踪和占用管理等应用程序.
- 该系统特别适用于历史建筑,博物馆和流行病后的环境,这些环境需要有效的监控和人群管理.
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