Location-Aware Construction

位置感知建设

• 批准号: 418752-2012
• 负责人: Razavi, Saiedeh
• 金额: $ 2.11万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=596496
• 关键词: Location; Aware; Construction

Construction projects can be managed more effectively if the locations of materials, equipment, and the workforce are continuously known. Location information is used to plan construction activities, work schedules, materials and equipment supply, site access, and other aspects such as safety and work-zone mobility. This research program will develop a framework to acquire location data from various sensors, analyze the overall situation in the context of the construction project, and provide improved information and decision support for construction participants. This "Location-Aware Construction" framework consists of tools that will integrate the knowledge of "location", "schedule", and "resource and activity interdependencies" within the specific construction processes. The research objectives will be achieved by utilizing a Sensing and Wireless Network Engine to acquire location information, and then developing a Location Awareness Engine that estimates and visually represents more reliable spatial information, a Cognitive Engine for knowledge management and assessment of interdependencies of activities and location of resources, and Location-based Application Engines. Advanced computation techniques will be used, including data fusion, learning and adaptation, soft computing (including fuzzy logic, probabilistic reasoning, and rough set theory), evidence based reasoning, belief function theory, evolutionary computing, and uncertainty management.

如果不断了解材料、设备和劳动力的位置，就可以更有效地管理建筑项目。位置信息用于计划施工活动、工作时间表、材料和设备供应、现场访问以及其他方面，如安全和工作区流动性。这项研究计划将开发一个框架，从各种传感器获取位置数据，在建设项目的背景下分析整体情况，并为施工参与者提供更好的信息和决策支持。这个“位置感知构建”框架由一些工具组成，这些工具将在特定的构建过程中整合有关“位置”、“进度”以及“资源和活动相互依赖”的知识。研究目标将通过利用传感和无线网络引擎获取位置信息，然后开发估计并直观地表示更可靠的空间信息的位置感知引擎，用于知识管理和评估活动与资源位置相互依赖的认知引擎，以及基于位置的应用引擎来实现。将使用先进的计算技术，包括数据融合、学习和适应、软计算(包括模糊逻辑、概率推理和粗糙集理论)、基于证据的推理、信念函数理论、进化计算和不确定性管理。