Automated Vision-Based Sensing for Site Operations Analysis

用于现场操作分析的基于视觉的自动化传感

• 批准号: 1030472
• 负责人: Patricio Vela
• 金额: $ 30万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1030472&HistoricalAwards=false
• 关键词: Automated; Vision; Based; Sensing; Site

This research seeks to prove that it is possible to reliably and automatically track work progress and multiple resources with images (video and/or time-lapse) in order to reproduce the daily workflow activities associated to a construction worksite. The task of measuring the progress of construction site activities that involve workers, large machines, and materials, has often been a subjective and intensive manual process that is prone to error and, in real operations, frequently out-of-date. Demonstrating that an active vision system can effectively analyze and assess work-site progress will assist project managers by reducing the time spent monitoring and interpreting project status and performance, thus enabling increased attention to control of cost and schedule. By making project management and workforce more aware of the performance status of their project and their work environment, potential savings to the industry are envisioned. The track data will be interpreted and used to provide understanding of the spatio-temporal evolution of a worksite for automatically generating knowledge about worksite operations. In an information-based framework, much effort is spent acquiring and interpreting information. In a knowledge-based framework, efforts are allocated to making decisions based on the interpreted information.If successful, this research will transform the review and management of construction operations from being information-based to knowledge-based, thus saving human resources and improving decision effectiveness. This research has broader appeal beyond construction. Research domains incorporating or requiring vision-based sensing, diverse resources (people, small to heavy machinery, goods, etc.), and processing of the visual data for awareness of operations and activities are additional investigation domains. Examples include airport ground operations and mining operations. Contributions are also expected in the fields of machine learning and computer vision. The proposed research will impact research into site operations by enabling the automated monitoring and tracking of site resources. Video-based monitoring and processing algorithms provide a non-intrusive, easy, and, rapid mechanism for generating a body of operational information and knowledge which, when made available, will enable inquiry into construction operations that is currently not possible. Longer term, this research will serve as a valuable aid to project management by enabling tighter control and greater efficiency. By making project management and workforce more aware of the performance status of their project and their work environment, potential savings to the construction and other industries are envisioned. This research will also actively include and drive the education of the next generation of engineers (civil, electrical, and computational engineering) and construction labor pool. The research has a dedicated outreach plan to involve in this research a broad spectrum of students from high schools and industry professionals who are interested in advanced hard- and software technology

这项研究试图证明，有可能通过图像(视频和/或时间推移)可靠地和自动地跟踪工作进度和多种资源，以便再现与建筑工地相关的日常工作流活动。测量涉及工人、大型机器和材料的施工现场活动的进度的任务通常是一个主观和密集的手工过程，容易出错，在实际操作中经常过时。证明一个积极的VISION系统可以有效地分析和评估工地进度，这将有助于项目经理减少监测和解释项目状态和业绩所花费的时间，从而提高对成本和进度控制的重视。通过让项目管理人员和员工更多地了解他们的项目的绩效状况和他们的工作环境，可以预见到为行业节省的潜在成本。轨道数据将被解释并用于提供对工地时空演变的理解，以自动生成关于工地作业的知识。在以信息为基础的框架中，获取和解释信息花费了大量的精力。在基于知识的框架下，努力根据解读的信息进行决策。如果成功，这项研究将把施工作业的审查和管理从基于信息的方式转变为基于知识的方式，从而节省人力资源，提高决策效率。这项研究具有比建筑更广泛的吸引力。其他研究领域包括或需要基于视觉的传感、不同的资源(人员、小型机械、重型机械、货物等)，以及为了解业务和活动而处理视觉数据。例子包括机场地面作业和采矿作业。预计还将在机器学习和计算机视觉领域做出贡献。拟议的研究将通过实现对场地资源的自动监测和跟踪，对场地作业的研究产生影响。基于视频的监控和处理算法提供了一种非侵入性、简单和快速的机制，用于生成一组操作信息和知识，当这些信息和知识可用时，将能够查询目前不可能进行的施工操作。从长远来看，这项研究将通过实现更严格的控制和更高的效率，为项目管理提供有价值的帮助。通过让项目管理人员和工作人员更多地了解他们项目的绩效状况和他们的工作环境，预计可以为建造业和其他行业节省开支。这项研究还将积极包括和推动下一代工程师(土木工程、电气和计算工程)和建筑劳动力的教育。这项研究有一个专门的推广计划，让来自高中的广泛学生和对先进的硬件和软件技术感兴趣的行业专业人士参与到这项研究中来