SUSTAIN: Sensor-based Unified Simulation Techniques for Advanced In-building Networks

SUSTAIN：用于高级室内网络的基于传感器的统一仿真技术

• 批准号: 521555-2018
• 负责人: Wainer, Gabriel
• 金额: $ 15.01万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=694580
• 关键词: SUSTAIN; Sensor; based; Unified; Simulation

Modern building automation systems collect and store vast amounts of data in temporal scales ranging from seconds to multiple years and spatial scales ranging from rooms to communities. But tools that facilitate management and visualization of these data are in their infancy. It has become abundantly clear that data availability alone has not significantly improved the way buildings are operated. Emphasis tends to be on presenting raw data, rather than providing new tools for improving building performance. The proposed research shall yield intuitive, informative, and educational visualization methods including Building Information Modeling (BIM) software, data acquisition and control, and advanced visualization. The research focuses on new mechanisms for integrating these different techniques, using simulation as the means for exploring different design options and improvement in building operations. We will define and develop new methods for the integration of real-time sensor data, occupancy information based on advanced wearable sensors and occupants' portable devices (and the buildings networks). These data will be combined with parametric information from the building to construct formal models that can be used for both simulation and control. The formal models will provide analytic results that will be then be used for a variety of simulations and later deployed in advanced 3D BIM visualization environments (at the building and campus levels). We will conduct real experimentation in the four test buildings at Carleton University. The results will be used by Autodesk Research in their BIM tools to allow Architecture, Engineering, Construction, and Operations (AECO) professionals to analyze real-time data and visualize the modeling results and the analysis results into their actual designs, improving the overall process.

现代楼宇自动化系统收集和存储从几秒到几年的时间尺度和从房间到社区的空间尺度的大量数据。但是，促进这些数据的管理和可视化的工具还处于起步阶段。很明显，数据的可用性本身并没有显著改善建筑物的运营方式。重点往往是呈现原始数据，而不是提供新的工具来改善建筑性能。拟议的研究应产生直观，信息丰富和教育可视化方法，包括建筑信息建模（BIM）软件，数据采集和控制，以及先进的可视化。研究重点是整合这些不同技术的新机制，使用模拟作为探索不同设计方案和改善建筑运营的手段。我们将定义和开发新的方法，用于实时传感器数据的集成，基于先进的可穿戴传感器和居住者的便携式设备（和建筑物网络）的占用信息。这些数据将与建筑物的参数信息相结合，以构建可用于模拟和控制的正式模型。正式模型将提供分析结果，然后用于各种模拟，并随后部署在高级3D BIM可视化环境中（在建筑和校园级别）。我们将在卡尔顿大学的四座测试大楼里进行真实的实验。Autodesk Research将在其BIM工具中使用这些结果，以使建筑、工程、施工和运营（AECO）专业人员能够分析实时数据，并将建模结果和分析结果可视化到他们的实际设计中，从而改善整体流程。