生成式人工智能大模型在工程建造领域的应用与挑战

Application and Challenges of Generative AI Large Models in Construction Engineering

摘要:

生成式人工智能大模型在工程建造领域面临专业认知不足、应用场景与流程不明确等挑战，为挖掘生成式人工智能大模型在建筑垂直领域的应用场景与工程价值，系统分析与梳理生成式人工智能大模型在我国工程建造领域的潜在应用与面临的挑战，通过文献调研、专家讨论、价值链分析方法，明确该技术在工程建造领域的应用现状，建立“Construction-3L”建造领域大模型应用框架，从通用模型层（L1）、行业模型层（L2）、场景模型层（L3）3个维度挖掘大模型技术在立项、设计、施工中的应用机会与价值赋能方式，提出工程建造场景大模型的构建流程，同时分析大模型在工程应用中算法、算据、评价机制方面的共性挑战，并展望了工程建造领域大模型的应用场景、技术创新、政策方向。

Abstract:

Generative artificial intelligence （AI） large models face challenges in the engineering construction domain， including insufficient domain-specific cognition and unclear application scenarios and undefined workflows. To explore the potential applications and engineering value of generative AI large models in the vertical field of construction ， this paper systematically analyzes and reviews their potential applications and challenges in China’s construction sector. Through literature review， expert consultations， and value-chain analysis， the current state of AI model applications in construction is clarified. A “Construction-3L” large-model application framework is established， consisting of three dimensions： the general model layer （L1）， the industry model layer （L2）， and the scenario model layer （L3）. Based on this framework， application opportunities and value-empowerment pathways of large-model technologies in the stages of project initiation， design， and construction are explored. A development workflow for construction-scenario large models is proposed. Furthermore， common challenges related to algorithms， data （computing evidence）， and evaluation mechanisms in engineering applications of large models are analyzed， and future prospects are discussed with respect to application scenarios， technological innovation， and policy directions in the engineering construction field.