Development of Key Domain-Relevant Technologies for Smart Construction in China

Smart construction integrates new-generation information technology with construction and is important for the highquality development of China’s construction industry. This study expounds the basic concept and importance of smart construction and summarizes four types of key domain-relevant technologies: engineering software for entire industrial chain integration, construction Internet of things for smart construction sites, intelligent construction machinery for man–machine integration, and construction big data for intelligent decision making. Subsequently, we analyze the current status and weaknesses of these technologies in terms of market environment, enterprise deployment, and core resource reserves through questionnaire survey and expert interview. Moreover, we identify the development goals and propose the major tasks, including establishing and improving the standards system; promoting cooperation among industry, universities, research institutes, and application; improving intellectual property protection; and conducting pilot demonstration of typical projects. Furthermore, suggestions are proposed from the perspectives of government, enterprises, and universities

Early-warning of unsafe hoisting operations: An integration of digital twin and knowledge graph

Unsafe hoisting operations have been consistently associated with numerous safety incidents involving tower cranes. Currently, the predominant measures to mitigate these operations center around comprehensive training and education, emphasizing standardized protocols prior to hoisting activities. Despite concerted efforts in this direction, a conspicuous research gap persists in early-warning mechanisms during the construction phase. This paper aims to address this gap by proposing an innovative early-warning methodology, inspired by the principles of digital twin and knowledge graph. We firstly introduce a digital twin framework designed to mirror the real-time operational status of the tower crane. This framework enables the immediate detection of deviations or infractions as they occur. Subsequently, we develop a knowledge graph capable of promptly identifying unsafe hoisting operations by leveraging real-time data obtained from the digital twin. To validate the efficacy of our proposed methodology, we construct a scaled-down replica of a tower crane and establish a tailored digital twin system. The findings of a series of experimental trials prominently underscore the system's capability to generate timely alerts in response to unsafe hoisting operations while maintaining an impressively low rate of false alarms