Human-Aware Environments for Distributed Building Systems Operations

分布式建筑系统运营的人性化环境

基本信息

项目摘要

Innovative management of urban infrastructure operations has a critical role in enhancing their serviceability, sustainability, and flexibility in integration of dynamic sources of energy. Buildings, a major component of the urban infrastructure, account for majority of energy consumption. This project investigates novel approaches for human-centered and distributed quantification of thermal demand in buildings for efficient thermal energy management. Conventional monitoring and control approaches in buildings are constrained with limited feedback from an environment as well as conservative assumptions that do not reflect the dynamics of their users. To address these limitations, this project investigates a closer system integration between human body thermal response and control mechanisms of building systems. Accordingly, the project investigates non-intrusive sensing and inference methodologies that enable a smart environment to infer the need of its occupants by considering the trade-off between instrumentation, feasibility, and performance. Realization of the research will provide the ground in identifying adaptation potentials at building level and building networks at grid level to improve serviceability of building infrastructure. By leveraging the cross-disciplinary nature of the research, this project integrates findings in undergraduate and graduate courses. It also contributes to the programs that encourage K-12 and undergraduate learners from groups underrepresented in engineering to pursue degrees in STEM fields in collaboration with Virginia Tech CEED center. Human body responses to ambient conditions, which are reflected in cardiopulmonary adjustments, act as a transmitter in an environment. This characteristic is leveraged in this project to shift from human-centric instrumentation for personalized thermal comfort assessment to space-centric by a novel application of Doppler radar systems that act as the sole transceivers. The fundamental requirements of feasibility and performance for a system integration will be investigated through experimental and field validation studies, mathematical modeling, and design of an alternative control framework. Statistical inference techniques, coupled with specialized signal processing frameworks will be developed to enable the application of human physiological response as sensor proxies for distributed feedback in control of building systems? operation. To this end, bio-signal feature engineering and sensitivity analyses will be carried out to develop efficient probabilistic models of thermal response feedback that account for environmental noise interference. Parametric and non-parametric techniques for modeling thermal response of human body will be also utilized to investigate new dimensions to standard thermal sensation metrics. Alternative control scenarios that combine real-time personalized feedback with existing control logic in building systems will be evaluated to (1) assess the efficacy of the control feedback from physiological responses and (2) identify potential energy efficiency improvements in buildings as the main research hypotheses.
城市基础设施运营的创新管理对于增强其在整合动态能源方面的适用性、可持续性和灵活性具有至关重要的作用。建筑是城市基础设施的主要组成部分,占能源消耗的大部分。该项目研究以人为中心和分布式量化建筑物热需求的新方法,以实现有效的热能管理。建筑物中的常规监测和控制方法受到来自环境的有限反馈以及不反映其用户动态的保守假设的限制。为了解决这些局限性,本项目研究了人体热响应和建筑系统控制机制之间更紧密的系统集成。因此,该项目研究非侵入式传感和推理方法,使智能环境能够通过考虑仪器、可行性和性能之间的权衡来推断其居住者的需求。这项研究的实现将为确定建筑层次的适应潜力和构建网格层次的网络以提高建筑基础设施的适用性提供基础。通过利用研究的跨学科性质,该项目整合了本科生和研究生课程的研究成果。它还为鼓励K-12和工程专业代表性不足群体的本科生与弗吉尼亚理工学院CEED中心合作攻读STEM领域学位的项目做出贡献。人体对周围环境条件的反应反映在心肺调节中,在环境中扮演着传递者的角色。该项目利用这一特点,通过使用作为唯一收发机的多普勒雷达系统的新应用,将以人为中心的个性化热舒适性评估工具转变为以空间为中心的工具。将通过实验和现场验证研究、数学建模和设计替代控制框架来研究系统集成的可行性和性能的基本要求。统计推断技术和专门的信号处理框架将被开发出来,以使人类生理反应作为分布式反馈的传感器代理应用于建筑系统的控制?手术。为此,将进行生物信号特征工程和灵敏度分析,以开发考虑环境噪声干扰的有效热响应反馈概率模型。用于模拟人体热响应的参数和非参数技术也将被用来研究标准热感觉度量的新维度。将评估将实时个性化反馈与建筑系统中现有控制逻辑相结合的替代控制场景,以(1)评估来自生理响应的控制反馈的有效性,以及(2)确定建筑中潜在的能效改进作为主要研究假设。

项目成果

期刊论文数量(17)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Vision-based thermal comfort quantification for HVAC control
  • DOI:
    10.1016/j.buildenv.2018.05.018
  • 发表时间:
    2018-09
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Wooyoung Jung;F. Jazizadeh
  • 通讯作者:
    Wooyoung Jung;F. Jazizadeh
Proactive Smart Home Assistants for Automation—User Characteristic-Based Preference Prediction with Machine Learning Techniques
  • DOI:
    10.1061/9780784483893.034
  • 发表时间:
    2022-05
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tianzhi He;F. Jazizadeh
  • 通讯作者:
    Tianzhi He;F. Jazizadeh
Feasibility Assessment of Heat Flux Sensors for Human-in-the-Loop HVAC Operations
热通量传感器在 HVAC 操作环路中的可行性评估
Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling
  • DOI:
    10.3390/s19173691
  • 发表时间:
    2019-08
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wooyoung Jung;F. Jazizadeh;T. Diller
  • 通讯作者:
    Wooyoung Jung;F. Jazizadeh;T. Diller
Energy saving potentials of integrating personal thermal comfort models for control of building systems: Comprehensive quantification through combinatorial consideration of influential parameters
  • DOI:
    10.1016/j.apenergy.2020.114882
  • 发表时间:
    2020-06
  • 期刊:
  • 影响因子:
    11.2
  • 作者:
    Wooyoung Jung;F. Jazizadeh
  • 通讯作者:
    Wooyoung Jung;F. Jazizadeh
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Farrokh Jazizadeh Karimi其他文献

Farrokh Jazizadeh Karimi的其他文献

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