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

点击翻译按钮获取中文摘要

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.