Human-Building Integration: Bio-Sensing Adaptive Environmental Control for Human Health and Sustainability

人建一体化：生物传感自适应环境控制促进人类健康和可持续发展

• 批准号: 1707068
• 负责人: Joon-Ho Choi
• 金额: $ 30万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1707068&HistoricalAwards=false
• 关键词: Human; Building; Integration; Bio; Sensing

1707068 (Choi). This research will develop an integrated human-centered framework for intelligent environmental control in a building. The physiological signals of the occupants, as well as their ambient environmental data, will be integrated by using sensing agents (such as wearable as well as remote sensors) and embedded environmental sensors in the building. This will enable bio-sensing-driven multi-criteria decisions for determining building thermal and lighting system controls that will potentially lower energy usage awhile improving occupant comfort. This human-centered approach will provide a framework that will 1) address sensor data processing and analysis challenges that are inherent in large and dynamic datasets generated from sensing agents; 2) develop methods for optimizing decisions and solutions to multiple-criteria problems pertaining to occupants' preferences; and 3) establish a human-centered control approach that is integrated with a conventional control system for building retrofits to enable real-time decision making and system optimization that will enhance energy efficient operations and occupants' comfort. Such a three-fold approach can lead to tailored building environmental control systems with the potential for dramatically improving the efficiency of a building's performance, increasing sustainability, and leveraging informatics technology that will improve the occupants' quality of life.

1707068（Choi）。本研究将发展一个以人为中心的建筑物智能环境控制的综合框架。居住者的生理信号，以及他们的周围环境数据，将通过使用传感代理（如可穿戴以及远程传感器）和嵌入式环境传感器在建筑物中集成。这将使生物传感驱动的多标准决策，用于确定建筑物的热和照明系统控制，这将潜在地降低能源使用，同时提高居住者的舒适度。这种以人为中心的方法将提供一个框架，该框架将1）解决传感器数据处理和分析挑战，这些挑战是由传感代理生成的大型动态数据集所固有的; 2）开发用于优化与居住者偏好有关的多标准问题的决策和解决方案的方法;以及3）建立以人为中心的控制方法，该方法与用于建筑物改造的传统控制系统集成，以实现真实的-时间决策和系统优化，将提高能源效率的运作和居住者的舒适度。这种三重方法可以导致定制的建筑物环境控制系统，其具有显著提高建筑物性能的效率、增加可持续性以及利用将提高居住者生活质量的信息技术的潜力。

项目成果

Investigation of a real-time change of human eye pupil sizes per visual sensation condition

研究每种视觉感觉条件下人眼瞳孔大小的实时变化

• 发表时间: 2018
• 期刊: ARCC - EAAE 2018 INTERNATIONAL CONFERENCE
• 作者: Choi, Joon-Ho;Lin, Xiaoxin;Schiller, Marc
• 通讯作者: Schiller, Marc

Investigation of a real-time change of human eye pupil sizes for visual environmental controls in the workplace environment

研究人眼瞳孔大小的实时变化，以实现工作场所环境中的视觉环境控制

• 发表时间: 2018
• 期刊: Indoor air quality and climate
• 作者: Choi, J.;Lin, X.
• 通讯作者: Lin, X.

Data-Driven Approach to Control Air Temperature Based on Facial Skin Temperature

基于面部皮肤温度控制气温的数据驱动方法

• 发表时间: 2020
• 期刊: Environmental engineering
• 作者: Jia, Mengqi;Choi, Joon-Ho
• 通讯作者: Choi, Joon-Ho

Development of the data-driven thermal satisfaction prediction model as a function of human physiological responses in a built environment

• DOI: 10.1016/j.buildenv.2019.01.007
• 发表时间: 2019-03
• 期刊: Building and Environment
• 影响因子: 7.4
• 作者: Joon-Ho Choi;D. Yeom

A Personal Visual Comfort Model: Predict Individual’s Visual Comfort Using Occupant Eye pupil Size and Machine Learning

个人视觉舒适度模型：使用占用者眼睛瞳孔大小和机器学习来预测个人的视觉舒适度

• DOI: 10.1088/1757-899x/609/4/042097
• 发表时间: 2019
• 期刊: IOP conference series
• 作者: Cen, Lingkai;Choi, Joon-Ho;Yao, Xiaomeng;Gil, Yolanda;Narayanan, Shrikanth;Pentz, Maryann
• 通讯作者: Pentz, Maryann