A Review on Intelligent Perception Technologies in Building Engineering

ZHOU Shuwei; XU Ke; LIU Yang

doi:10.3724/j.gyjzG25072701

Volume 56 Issue 8

Aug. 2026

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ZHOU Shuwei, XU Ke, LIU Yang. A Review on Intelligent Perception Technologies in Building Engineering[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(8): 193-206. doi: 10.3724/j.gyjzG25072701

Citation:

ZHOU Shuwei, XU Ke, LIU Yang. A Review on Intelligent Perception Technologies in Building Engineering[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(8): 193-206. doi: 10.3724/j.gyjzG25072701

ZHOU Shuwei, XU Ke, LIU Yang. A Review on Intelligent Perception Technologies in Building Engineering[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(8): 193-206. doi: 10.3724/j.gyjzG25072701

Citation:

ZHOU Shuwei, XU Ke, LIU Yang. A Review on Intelligent Perception Technologies in Building Engineering[J]. INDUSTRIAL CONSTRUCTION, 2026, 56(8): 193-206. doi: 10.3724/j.gyjzG25072701

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A Review on Intelligent Perception Technologies in Building Engineering

doi: 10.3724/j.gyjzG25072701

1. Xuchang Urban Rail Transit Co., Ltd., Xuchang 461000, China;
2. College of Civil Engineering, Xuchang University, Xuchang 461000, China;
3. Engineering Technology Research Center for Ecological and High-Quality Utilization of Construction Solid Waste, Xuchang 461000, China

Received Date: 2025-07-27
Available Online: 2026-11-06

Abstract

Abstract

With the ongoing digital transformation in the construction industry， construction sites are generating large volumes of heterogeneous and dynamically evolving data from multiple sources， including text， images， speech， and sensors. Traditional rule-based analytical methods are insufficient to fully exploit the complementary information across different modalities and fail to meet the demands of real-time perception and collaborative decision-making. This paper adopted a structured framework consisting of input， task， fusion， challenge， and prospect to systematically review the characteristics of four primary types of modal inputs in construction scenarios and their corresponding task mappings. It analyzed typical applications of multimodal artificial intelligence （AI） in critical functions such as safety monitoring， progress tracking， equipment maintenance， and document processing， demonstrating its value in semantic extraction， behavior recognition， and status modeling. Moreover， it summarized three major fusion strategies at the data， feature， and decision levels， and discussed their technical principles and applicable contexts. The evolution of collaborative system architectures involving edge， cloud， and on-site devices was examined， along with an overview of significant technical challenges， including data heterogeneity， poor model transferability， limited computational resources， and compliance with data privacy regulations. Finally， this paper proposed future research directions， including the integration of domain knowledge， optimization of edge deployment， and reinforcement of standardization efforts， to provide a systematic reference for the ongoing advancement of multimodal AI in intelligent construction.
- intelligent construction,
- multimodal artificial intelligence,
- construction site perception,
- data fusion,
- construction management,
- semantic understanding

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References(116)

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