Scalable Cyber-Physical-Human Systems for Intelligent and Interactive Buildings

适用于智能交互式建筑的可扩展网络物理人类系统

• 批准号: RGPIN-2022-04453
• 负责人: Lee, Seungjae
• 金额: $ 1.97万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=748872
• 关键词: Scalable; Cyber; Physical; Human; Systems

The building sector accounts for about 30% of Canada's total end-use energy consumption, while Canadians spend 90% of their time indoors. In this context, equipping buildings with human interactive intelligent systems, i.e., cyber-physical-human systems (CPHSs), has received attention as a cost-effective solution to improve building energy performance and indoor environmental quality (IEQ). The long-term vision of the proposed research program is to mitigate climate change and advance the quality of life through the realization of intelligent and interactive buildings. Towards this vision, my approach is to pursue seamless integration of domain knowledge and machine learning (ML) to develop effective, reliable, and scalable AI-based CPHSs for intelligent and interactive buildings. Over the next five years, the overall objective of the proposed research program is to conclusively determine and demonstrate the efficacy of my pioneering approach that integrates domain knowledge and ML in developing AI-based CPHSs for intelligent and interactive buildings. My focus will initially be on office building operations. The corresponding short-term objectives are to: (1)Develop a knowledge modelling framework that enables encoding of existing building domain knowledge into CPHSs and facilitates knowledge-informed ML; (2)Develop a causal inference framework that allows investigating new causal knowledge related to occupants' needs, behaviours, and their corresponding decision-making processes; (3)Develop and demonstrate a CPHS for intelligent and interactive buildings, equipped with (i) a scalable adaptive optimal controller and (ii) an advanced user interface with an effective feedback/incentive program, by utilizing the frameworks described in Objective 1 and 2. The proposed research will revolutionize the building automation industry so that intelligent and interactive buildings become commodities resulting in a profound impact on the energy sectors in Canada. In addition, the research will contribute to advancing the quality of life in Canada with improved IEQ. The successful completion of the objectives will be a breakthrough in CPHS research, in general, and building automation and management, in particular. The proposed research will also contribute to the interdisciplinary training of highly qualified personnel who will gain knowledge and skills in two domains: (i) building energy system and occupant and (ii) machine learning, optimal control, and human-machine interaction. The unique expertise HQP acquires will allow them to take a significant role in bridging these two domains and contribute to improving building energy performance and indoor environmental quality by applying modern AI solutions to buildings.

建筑行业约占加拿大终端能源消耗总量的30%，而加拿大人90%的时间是在室内度过的。在这种背景下，为建筑物配备人机交互智能系统，即网络-物理-人系统（CPHSs），作为提高建筑能源性能和室内环境质量（IEQ）的成本效益解决方案而受到关注。该研究项目的长期愿景是通过实现智能和互动建筑来缓解气候变化，提高生活质量。为了实现这一愿景，我的方法是追求领域知识和机器学习（ML）的无缝集成，为智能和交互式建筑开发有效、可靠和可扩展的基于ai的cpss。在接下来的五年里，拟议研究计划的总体目标是最终确定并证明我的开创性方法的有效性，该方法将领域知识和ML集成在为智能和交互式建筑开发基于人工智能的cpss中。我最初的工作重点是办公楼的运营。相应的短期目标是：(1)开发一个知识建模框架，使现有的建筑领域知识编码到cpss中，并促进知识知情的机器学习；(2)建立一个因果推理框架，允许调查与居住者需求、行为及其相应决策过程相关的新因果知识；(3)利用目标1和2所述的框架，为智能和交互式建筑开发和演示一种CPHS，配备(i)可扩展的自适应最优控制器和（ii）具有有效反馈/激励计划的高级用户界面。拟议的研究将彻底改变建筑自动化行业，使智能和交互式建筑成为商品，从而对加拿大的能源部门产生深远的影响。此外，该研究将有助于提高加拿大的生活质量，改善IEQ。这些目标的成功完成，将是公共卫生服务研究的一个突破，特别是楼宇自动化和管理。拟议的研究也将有助于高素质人才的跨学科培训，他们将获得两个领域的知识和技能：(i)建筑能源系统和居住者；（ii）机器学习，最优控制和人机交互。HQP获得的独特专业知识将使他们能够在连接这两个领域方面发挥重要作用，并通过将现代人工智能解决方案应用于建筑，为提高建筑能源性能和室内环境质量做出贡献。