Digital Technologies for Automated Quality Verification of Construction Material Deliveries Based on IoT, BIM, and AI Integration
Keywords:
artificial intelligence, control, materials, concrete, automated verification, digital twinAbstract
The article addresses the problem of improving the reliability and efficiency of quality control of construction materials during their delivery to construction sites in the context of digital transformation of the construction industry. It is shown that traditional acceptance methods based on compliance certificates, selective laboratory testing, and visual inspection are highly dependent on the human factor, fragmented in nature, and unable to account for dynamic changes in material properties. These limitations are especially critical for materials with variable physical and mechanical characteristics, such as concrete mixtures. The purpose of the study is to develop an integrated approach to automated verification of construction material deliveries based on the combined use of Internet of Things (IoT), Building Information Modeling (BIM), and Artificial Intelligence (AI). The paper proposes a digital quality control architecture that enables continuous real-time acquisition of sensor data, their integration into a BIM-based information environment, and intelligent analysis with automated “accept/reject” decision-making without direct human involvement.
The quality control process is formalized as a dynamic state estimation problem using a state-space model and a recursive Kalman filtering algorithm, which allows measurement uncertainty and external influencing factors during transportation to be taken into account. A generalized deviation index from design and regulatory parameters is introduced as the basis for automated decision-making.
Simulation results of concrete mixture delivery confirm the feasibility of the proposed approach. The methodology reduces inspection time, improves the detection of non-compliant material batches, and ensures digital traceability of material flows within the BIM environment. The results demonstrate the potential of integrated IoT–BIM–AI systems as a key element of the Construction 4.0 concept and a foundation for further development of digital twins of logistics and construction processes.
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