I-Corps: Automated Activity Monitoring of Construction Machinery Using a Hybrid Approach

这个i-Corps项目的更广泛的影响/商业潜力将是为施工经理和设备所有者提供一个经济高效且易于使用的工具，以监控其机器的性能，测量生产率和已完成工作的数量，记录活动和空闲时间，并识别异常情况，以考虑预防/纠正措施。该系统最终将在建设项目中的所有设备部件上运行，并将生成有关该项目的必要管理信息。该项目预计将对“建筑设备监控”的概念进行一次革命性的重新思考，并将其从“位置跟踪”工具转变为信息量大的“性能监控系统”。考虑到维护/维修/燃料/操作员费用在建筑重型设备总成本中的巨大成本，该技术可以为美国建筑、工程和建筑行业节省大量成本。该项目的活动将在犹他州的盐湖城进行，盐湖城是美国新兴的科技创业中心之一，也是快速建设的地点。这可能有助于该项目的商业化阶段，并提供极好的教育和培训机会，特别是对参与该项目的研究生而言。该i-Corps项目旨在开发和实证测试用于自动检测、跟踪和记录建筑重型设备活动的混合系统的可行性。该系统的工作原理是使用专门设计的硬件单元收集工程机械的音频、运动学和位置数据。收集的数据将通过Wi-Fi链路传输到中央处理单元，并在每个工作班次期间自动生成按时间顺序的活动和生产率列表。下一步，将进一步整合和处理从单个机器收集和处理的信息，以生成项目和公司层面的管理信息。该项目的创新方面有两个方面：1)混合使用音频和运动信号，能够产生更准确的结果，并克服单独实施每个信号的限制和障碍；2)融合来自多台机器的信息并自动生成整个项目(和公司)的管理信息的概念，可以取代目前更新项目时间表、预算和库存管理系统的人工程序。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project will be to provide a cost-efficient, and easy-to-use tool for construction managers and equipment owners to monitor performance of their machines, measure productivity rates and quantities of completed work, record active vs. idle times, and recognize abnormal conditions for considering preventive/corrective actions. The system will eventually operate on all equipment pieces in a construction project and necessary managerial information about the project will be generated. The project is expected to provide a transformational re-thinking about the concept of "construction equipment monitoring" and translate it from "location tracking" tools into informative "performance monitoring and control systems." Considering the significant costs of maintenance/repair/fuel/operator expenses in overall costs of construction heavy equipment, the technology can provide considerable savings to the U.S. architecture, engineering, and construction industries. Activities of this project will take place in Salt Lake City, Utah, one of America's emerging tech startup hubs and a setting for rapid construction. This may facilitate the commercialization phase of the project and also provide excellent educational and training opportunities, especially for the graduate student involved in the project. This I-Corps project aims to develop and empirically test the feasibility of a hybrid system for automatically detecting, tracking, and recording activities of construction heavy equipment. The system works based on collecting audio, kinematic, and location data of construction machines using a specially designed hardware unit. The collected data will be transferred into a central processing unit through Wi-Fi links and a chronological list of activities and productivity rates will be automatically generated during each working shift. As the next step, the information collected and processed from individual machines will be further integrated and processed to generate managerial information at project and company levels. The novel aspects of the project are twofold: 1) The hybrid use of audio and kinematic signals capable of producing more accurate results and overcoming the limitations and barriers of implementing each signal individually; and 2) the concept of fusing information from multiple machines and automatically generating managerial information for the entire project (and company), which could replace the current manual procedures for updating the project schedule, budget, and inventory management systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.