Collaborative Research: An Audio-Based Spatiotemporal System for Automated Monitoring of Construction Operations

协作研究：用于自动监控施工作业的基于音频的时空系统

• 批准号: 1537254
• 负责人: Abbas Rashidi
• 金额: $ 19万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1537254&HistoricalAwards=false
• 关键词: Collaborative; Research; Audio; Based; Spatiotemporal

The construction industry has been suffering from the lack of real-time performance monitoring, holistic project management, labor efficiency, and waste-preventive tools. This has led to cost overruns in almost 90 percent of construction projects with an average of 28 percent higher than forecast costs. This research project is expected to facilitate a transformative change in the ways that construction activities and operations are tracked and monitored. It will play a significant role in future rapid, nonintrusive and cost effective data acquisition capacity due to the use of audio signals instead of active sensors or digital cameras. Eventually the incurred efficiencies, sustainability benefits, and reduced costs of an automated project monitoring system will significantly benefit the U.S. Architecture, Engineering, Construction and Facilities Management industry. Success in this project also promises significant impacts to engineering education. The project's educational activities are highly integrated and inter-related with the research activities. The research results will be used to create educational material and will be made publicly available to educators at other institutions. The research results will also be integrated into the outreach and engagement activities and will result in engaging minorities and underrepresented groups through various programs.Despite recent advances in developing and implementing audio signal processing techniques for analyzing and modeling complex systems and processes, the real added value and potential applications of audio signals are still unknown to the civil engineering research community. This project is the first attempt to introduce audio signals as an alternative source of information for recognizing, tracking and monitoring construction operations at jobsites. Current approaches for recognizing and monitoring construction operations are either location-based or machine-vision-based, and implying audio signals is a significant leap to overcome their limitations. The framework provides the missing link between generic signal processing and construction performance monitoring. This project will expand the research horizons for academics in civil infrastructure systems as well as in digital signal processing domains. Particularly, this scientific breakthrough will set the stage for future research in automatically identifying and life-logging construction operations and equipment actions, estimating project performance indices, and creating corrective measures to keep the project performance as planned. This, in turn, will enable the future development of novel, automated applications for construction sequence analysis, productivity measuring, project monitoring and control systems, and maintenance decision making.

建设行业一直缺乏实时绩效监控、整体项目管理、劳动效率和预防浪费的工具。这导致近90%的建设项目成本超支，平均比预期成本高出28%。预计该研究项目将促进对建筑活动和作业的跟踪和监测方式的变革。由于使用音频信号代替有源传感器或数码相机，它将在未来快速、非侵入式和经济有效的数据采集能力中发挥重要作用。最终，自动化项目监控系统产生的效率、可持续性效益和降低的成本将极大地造福于美国的建筑、工程、建设和设施管理行业。该项目的成功也将对工程教育产生重大影响。该项目的教育活动与研究活动高度整合和相互关联。研究结果将用于制作教育材料，并将向其他机构的教育工作者公开提供。研究结果还将纳入外联和参与活动，并将通过各种方案吸引少数民族和代表性不足的群体。尽管最近在开发和实施用于分析和建模复杂系统和过程的音频信号处理技术方面取得了进展，但土木工程研究界仍然不知道音频信号的真正附加价值和潜在应用。该项目首次尝试将音频信号作为识别、跟踪和监测工地施工的另一种信息来源。目前识别和监控施工作业的方法要么是基于位置的，要么是基于机器视觉的，而暗示音频信号是克服其局限性的重大飞跃。该框架提供了通用信号处理和施工性能监测之间缺失的环节。该项目将为民用基础设施系统和数字信号处理领域的学者拓展研究视野。特别是，这一科学突破将为未来的研究奠定基础，包括自动识别和记录施工作业和设备动作，估算项目绩效指标，制定纠正措施以保持项目按计划进行。反过来，这将使未来开发新的、自动化的应用程序，用于施工顺序分析、生产力测量、项目监控系统和维护决策。