智慧工地之技术分析与展望
(1.哈尔滨工业大学,黑龙江 哈尔滨 150090;2.龙建路桥股份有限公司,黑龙江 哈尔滨 150001)
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摘要:面向建筑业激烈竞争态势与行业转型升级的迫切需求,智慧工地在技术推动与政策扶持下成为建筑业高质量发展的关键驱动力。本文通过解析智慧工地现有技术,划分数据采集、传输、存储与处理的关键技术架构及实际应用场景,揭示智慧工地如何通过技术创新实现资源、质量、安全、进度、环境等多维管理目标,剖析现有技术应用面临的挑战,并对未来技术发展趋势进行展望。关键词:智慧工地;技术应用;施工项目管理;建筑市场Abstract:In response to the intense competition in the construction industry and the urgent need for industrial transformation and upgrading,smart construction sites have become a key driver of high-quality development in the construction sector,driven by technological advancements and policy support. This paper analyzes existing technologies at smart construction sites,categorizing the critical technological architecture for data collection,transmission,storage,and processing,along with practical application scenarios. It reveals how technological innovation enables multi-dimensional management objectives such as resource utilization,quality,safety,progress,and environmental protection. The paper also examines the challenges faced in the application of current technologies and provides an outlook on future technological trends.Keywords:smart construction site;technology application;construction project management;construction market参考文献[1] 毛志兵.智慧建造决定建筑业的未来[J].建筑,2019(16):22-24.[2] Edirisinghe R. Digital skin of the construction site Smart sensor technologies towards the future smart construction site[J]. Engineering Construction and Architectural Management,2019(2):184-223.[3] Kim J,Chi S. Multi-camera vision-based productivity monitoring of earthmoving operations[J]. Automation in Construction,2020,112.[4] Liu Z,Meng X,Xing Z,etal. Digital Twin-Based Safety Risk Coupling of Prefabricated Building Hoisting[J]. Sensors,2021(11).[5] Jiang Y,He X. Overview of Applications of the Sensor Technologies for Construction Machinery[J]. IEEE Access,2020,8:110324-110335.[6] 孙昊,韩豫,马国鑫,等.融合BIM和RFID的建筑工人智能管理系统[J].工程管理学报,2017(2):95-99.[7] Cho Y K,Youn J H,Martinez D. Error modeling for an untethered ultra-wideband system for construction indoor asset tracking[J]. Automation in Construction,2010(1):43-54.[8] 闫文娟,王水璋.无人机倾斜摄影航测技术与BIM结合在智慧工地系统中的应用[J].电子测量与仪器学报,2019(10):59-65.[9] Jiang H,Lin P,Qiang M,etal. A labor consumption measurement system based on real-time tracking technology for dam construction site[J]. Automation in Construction,2015,52:1-15.[10] Chi H L,Kim M K,Liu K Z,etal. Rebar inspection integrating augmented reality and laser scanning[J]. Automation in Construction,2022,136:104183.[11] Pregnolato M,Gunner S,Voyagaki E,etal. Towards Civil Engineering 4.0:Concept,workflow and application of Digital Twins for existing infrastructure[J]. Automation in Construction,2022,141:104421.[12] M. Das J C C S. BIMCloud:A Distributed Cloud-Based Social BIM Framework for Project Collaboration[J]. Computing in Civil and Building Engineering,(2014). 2014:41-48.[13] Lin J,Hu Z,Zhang J,etal. A Natural-Language-Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM[J]. Computer-Aided Civil and Infrastructure Engineering,2016(1):18-33.[14] Lu W,Wu L,Xu J,etal. Construction E-Inspection 2.0 in the COVID-19 Pandemic Era:A Blockchain-Based Technical Solution[J]. Journal of Management in Engineering,2022(4).[15] Kim M,Cheng J C P,Sohn H,etal. A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning[J]. Automation in Construction,2015,49:225-238.[16] Huang L,Pradhan R,Dutta S,etal. BIM4D-based scheduling for assembling and lifting in precast-enabled construction[J]. Automation in Construction,2022,133.[17] Hartmann T,van Meerveld H,Vossebeld N,etal. Aligning building information model tools and construction management methods[J]. Automation in Construction,2012,22:605-613.[18] 刘占省,刘子圣,孙佳佳,等.基于数字孪生的智能建造方法及模型试验[J].建筑结构学报,2021(6):26-36.[19] Getuli V,Capone P,Bruttini A,etal. BIM-based immersive Virtual Reality for construction workspace planning:A safety-oriented approach[J]. Automation in Construction,2020,114.[20] Bao L,Van Tien Tran S,Nguyen T L,etal. Cross-platform virtual reality for real-time construction safety training using immersive web and industry foundation classes[J]. Automation in Construction,2022,143.[21] Mneymneh B E,Abbas M,Khoury H. Vision-Based Framework for Intelligent Monitoring of Hardhat Wearing on Construction Sites[J]. Journal of Computing in Civil Engineering,2019(2).[22] Golparvar-Fard M,Pena-Mora F,Savarese S. Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models[J]. Journal of Computing in Civil Engineering,2015(1).[23] Kassem M,Mahamedi E,Rogage K,etal. Measuring and benchmarking the productivity of excavators in infrastructure projects:A deep neural network approach[J]. Automation in Construction,2021,124.[24] Fang Q,Castro-Lacouture D,Li C Q. Smart Safety:Big Data-Enabled System for Analysis and Management of Unsafe Behavior by Construction Workers[J]. Journal of Management in Engineering,2024(1).[25] Yu Z,Gong Y. ChatGPT,AI-generated content,and engineering management[J]. Frontiers of Engineering Management,2024(1):159-166.[26] Ma Z,Cai S,Mao N,etal. Construction quality management based on a collaborative system using BIM and indoor positioning[J]. Automation in Construction,2018,92:35-45.[27] Fang W,Ding L,Zhong B,etal. Automated detection of workers and heavy equipment on construction sites:A convolutional neural network approach[J]. Advanced Engineering Informatics,2018,37:139-149.[28] Ning X,Qi J,Wu C,etal. Reducing noise pollution by planning construction site layout via a multi-objective optimization model[J]. Journal of Cleaner Production,2019,222:218-230.[29] 刘必君,叶雨辰.基于栈式降噪自动编码器的建筑工程施工成本预测[J].同济大学学报(自然科学版),2020(6):922-928.建筑经济,2025(4):26-33