Automated Activity Identification and Productivity Improvement in Construction using Computer Vision

建筑业经常被认为在自动化操作和提高生产率方面落后于其他行业。造成这一失误的一些挑战是施工环境的崎岖，以及场地边界的扩大。本研究的目的是创建自动化系统，以最少的人为干预来跟踪施工活动。这将促进应用程序模块的开发，这些模块可以：

Construction is regularly cited as lagging behind other industries in its effort to automate operations and improve productivity. Some of the challenges that contribute to this lapse are the rugged environment in which construction takes place, and the expanse of the site boundaries. The objective of this research is to create automated systems to track construction activities with a minimum of human intervention. This will facilitate the development of application modules that can: - Identify operational bottlenecks and use innovative optimization routines to suggest improvements - Identify inefficiencies and unnecessary idling to increase profitability and reduce emissions from equipment - Extend the technology to include night vision and operations in emergency zones Challenges in the research include ensuring that the technologies can withstand the the rugged environment of application areas (e.g. construction and open pit mining), and developing resilient algorithms that can self-correct due to camera movement or errors in identification. Ultimately, the system may be used to control unmanned equipment fleets in extreme environments.