Construction site management is a common direction of artificial intelligence in the engineering field. The application of artificial intelligence technology can improve the safety level of workers and optimize construction. Jun WANG et al. proposed three blockchain-based applications for improving the existing processes in contract management, supply chain management, and equipment leasing. Hakob AVETISYAN et al. established a mathematical model based on the previous successfully developed decision support model of construction equipment selection. This model was combined with a web server to select optimal construction equipment for a construction site while considering cost-, availability-, and transportation-related issues. Xincong YANG et al. proposed the use of biomechanical models and machine learning methods to identify human joints from video or images automatically that could provide a reliable basis for predicting the impact of construction activities on the safety and health of construction workers. Qixiang FAN pointed out that the Jinsha River Xiluodu Hydropower Plant utilized a variety of intelligent construction techniques, such as precision blasting, digital grouting, intelligent concrete pouring, and intelligent water cooling technology, to overcome many technical problems; Hongtao ZHOU et al. proposed a new construction site management mode for intelligent construction sites of large-scale construction projects with the ultimate goal of achieving safe, efficient, and high-quality construction. Bahaa Eddine MNEYMNEH et al. evaluated computer vision algorithms, particularly target detection and color-based segmentation methods, to detect helmets in the site effectively and rapidly. Yu ZHONG introduced the technical innovation of Sanyang Road Long River Tunnel Project in Wuhan that uses BIM-based digital management and control key technologies to achieve construction scheme optimization, monitoring of construction quality and schedule, and error monitoring during construction.