SUSTAIN: Sensor-based Unified Simulation Techniques for Advanced In-building Networks
SUSTAIN: Sensor-based Unified Simulation Techniques for Advanced In-building Networks
批准号:
521555-2018
负责人:
Wainer, Gabriel
金额:
$14.93万
依托单位:
依托单位国家:
加拿大
项目类别:
Strategic Projects - Group
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31
中文摘要
现代楼宇自动化系统收集和存储从数秒到数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,便于管理和可视化这些数据的工具还处于起步阶段。很明显,仅凭数据可用性并不能显著改善建筑物的运营方式。重点往往是呈现原始数据,而不是提供改善建筑性能的新工具。拟议的研究应产生直观,信息丰富,具有教育意义的可视化方法,包括建筑信息模型(BIM)软件,数据采集和控制,以及高级可视化。研究的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选择和改进建筑操作的手段。我们将定义和开发新的方法,用于集成实时传感器数据、基于先进可穿戴传感器和居住者便携式设备(以及建筑物网络)的占用信息。这些数据将与来自建筑物的参数信息相结合,以构建可用于仿真和控制的正式模型。正式模型将提供分析结果,然后将用于各种模拟,然后部署在先进的3D BIM可视化环境中(在建筑和校园层面)。我们将在卡尔顿大学的四座测试大楼中进行真实的实验。这些结果将被欧特克研究中心用于他们的BIM工具中,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,从而改进整个过程。
英文摘要
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.
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会议论文
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批准号:521555-2018
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项目类别:Discovery Grants Program - Individual
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资助金额:$3.64万
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批准号:551055-2020
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项目类别:Alliance Grants
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资助金额:$3.64万
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负责人:Wainer, Gabriel
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依托单位:
Integration of analytical COVID-19 models for remote execution and advanced visualization for improved decision making
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批准号:551070-2020
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资助金额:$3.64万
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负责人:Wainer, Gabriel
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依托单位:
Modeling frameworks for spectrum sharing and channel reconstruction in 5G systems
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批准号:556819-2020
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项目类别:Alliance Grants
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资助金额:$5.83万
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财政年份:2020
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负责人:Wainer, Gabriel
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依托单位:
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项目类别:Discovery Grants Program - Individual
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资助金额:$3.64万
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财政年份:2019
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SUSTAIN: Sensor-based Unified Simulation Techniques for Advanced In-building Networks
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批准号:521555-2018
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项目类别:Strategic Projects - Group
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资助金额:$15.01万
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负责人:Wainer, Gabriel
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依托单位:
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项目类别:Discovery Grants Program - Individual
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资助金额:$3.64万
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财政年份:2018
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依托单位:
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资助金额:$1.82万
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负责人:Wainer, Gabriel
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依托单位:
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批准号:RGPIN-2015-06204
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资助金额:$3.64万
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财政年份:2017
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依托单位:
Advanced Methodologies for Real-Time Discrete Event Modelling and Simulation
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资助金额:$3.64万
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财政年份:2016
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依托单位:
Advanced Methodologies for Real-Time Discrete Event Modelling and Simulation
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批准号:RGPIN-2015-06204
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项目类别:Discovery Grants Program - Individual
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财政年份:2015
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Pedestrian modeling to ensure business continuity with public transit investment
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批准号:471039-2014
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资助金额:$1.82万
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依托单位:
Advanced Distributed Algorithms for COMP in LTE networks
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批准号:452608-2013
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Semantic Interoperabiliity for SageTea
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项目类别:Engage Grants Program
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资助金额:$1.82万
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Methodologies for real-time discrete-event simulation
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资助金额:$2.26万
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国内基金
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负责人:郑晓峰
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