• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers >Context-driven monitoring and control of buildings ventilation systems using big data and Internet of Things-based technologies
【24h】

Context-driven monitoring and control of buildings ventilation systems using big data and Internet of Things-based technologies

机译：使用大数据和基于物联网的技术，根据上下文驱动的建筑物通风系统的监控

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Ventilation systems are deployed in buildings to maintain good indoor air quality, especially in specific periods, or in the absence of buildings' windows. These systems perform automatically this task by regulating the injected air according to the actual indoor CO2 concentration. Several control approaches have been implemented and deployed in real-setting scenarios, but most of them are either time-triggered or based on fixed threshold values. In this paper, we introduce a platform that integrates recent advanced Internet of Things and big-data technologies for context-driven monitoring and control of ventilation systems. The aim is to gather, process and extract contextual data, mainly indoor/outdoor CO2 concentration, to be used for maintaining a suitable ventilation rate that balances between energy consumption and occupants' well-being. A prototype was developed and deployed for conducting experiments of different ventilation control approaches. We have developed two control approaches, ON/OFF and proportional-integral-derivative control, and compared them with the proposed state-feedback control approach. Experiments have been conducted in our Energy-Efficient Building Laboratory to evaluate these approaches in terms of the indoor CO2 concentration, the ventilation rates, and the power consumption. The experimental results show that the state-feedback control outperforms proportional-integral-derivative and ON/OFF control approaches in terms of energy efficiency and comfort.
机译：在建筑物中部署了通风系统，以保持良好的室内空气质量，尤其是在特定时期或没有建筑物窗户的情况下。这些系统通过根据实际室内CO2浓度调节注入的空气来自动执行此任务。已经在实际设置的场景中实现并部署了几种控制方法，但是大多数方法都是时间触发的或基于固定阈值的。在本文中，我们介绍了一个平台，该平台集成了最新的高级物联网和大数据技术，用于环境驱动的通风系统监视和控制。目的是收集，处理和提取背景数据，主要是室内/室外CO2浓度，以保持合适的通风率，从而在能耗和居住者的福祉之间取得平衡。开发并部署了一个原型，用于进行不同通风控制方法的实验。我们已经开发了两种控制方法，开/关和比例积分微分控制，并将它们与建议的状态反馈控制方法进行了比较。在我们的节能建筑实验室中进行了实验，以评估室内二氧化碳浓度，通风率和功耗方面的这些方法。实验结果表明，在能量效率和舒适性方面，状态反馈控制优于比例积分微分和ON / OFF控制方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号