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An information technology enabled sustainability test-bed (ITEST) for occupancy detection through an environmental sensing network

机译:信息技术使可持续性测试台(ITEST)能够通过环境传感网络进行占用检测

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摘要

This paper describes a large-scale wireless and wired environmental sensor network test-bed and its application to occupancy detection in an open-plan office building. Detection of occupant presence has been used extensively in built environments for applications such as demand-controlled ventilation and security; however, the ability to discern the actual number of people in a room is beyond the scope of current sensing techniques. To address this problem, a complex sensor network is deployed in the Robert L. Preger Intelligent Workplace comprising a wireless ambient-sensing system, a wired carbon dioxide sensing system, and a wired indoor air quality sensing system. A wired camera network is implemented as well for establishing true occupancy levels to be used as ground truth information for deriving algorithmic relationships with the environment conditions. To our knowledge, this extensive and diverse ambient-sensing infrastructure of the ITEST setup as well as the continuous data-collection capability is unprecedented. Final results indicate that there are significant correlations between measured environmental conditions and occupancy status. An average of 73% accuracy on the occupancy number detection was achieved by Hidden Markov Models during testing periods. This paper serves as an exploration to the research of ITEST for occupancy detection in offices. In addition, its utility extends to a wide variety of other building technology research areas such as human-centered environmental control, security, energy efficient and sustainable green buildings.
机译:本文描述了一个大型无线和有线环境传感器网络测试平台及其在开放式办公大楼中的占用检测中的应用。在建筑环境中已广泛使用乘员检测,用于需求控制通风和安全性等应用;但是,识别房间中实际人数的能力超出了当前传感技术的范围。为了解决该问题,在罗伯特·普雷格(Robert L. Preger)智能工作场所中部署了一个复杂的传感器网络,该网络包括无线环境传感系统,有线二氧化碳传感系统和有线室内空气质量传感系统。还实现了有线摄像机网络以建立真实的占用水平,以用作地面真实信息,以得出与环境条件的算法关系。据我们所知,ITEST设置的这种广泛而多样的环境传感基础设施以及连续的数据收集功能是前所未有的。最终结果表明,测得的环境条件与占用状态之间存在显着相关性。在测试期间,Hidden Markov模型在入住人数检测上的平均准确性达到了73%。本文是对ITEST办公人员占用检测研究的探索。此外,它的用途还扩展到了其他许多建筑技术研究领域,例如以人为中心的环境控制,安全性,节能和可持续的绿色建筑。

著录项

  • 来源
    《Energy and Buildings》 |2010年第7期|p.1038-1046|共9页
  • 作者单位

    Center for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;

    Research and Technology Center, Robert BOSCH LLC, Pittsburgh, PA 15212, USA;

    rnCenter for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;

    Research and Technology Center, Robert BOSCH LLC, Pittsburgh, PA 15212, USA;

    rnCenter for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;

    rnCenter for Building Performance and Diagnostics, Carnegie Mellon University, Pittsburgh, PA 15213, USA;

    Research and Technology Center, Robert BOSCH LLC, Pittsburgh, PA 15212, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    occupancy detection; sensor network; hidden markov model; open-plan office; human behavior;

    机译:占用检测;传感器网络隐藏的马尔可夫模型;开放式办公室;人类行为;

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