Intell. Infrastruct. Constr., Volume 1, Issue 3 (December 2025) – 2 articles

This study presents a nonlinear regression expansion model tailored to the characteristics of fissured highly expansive soils. Through in-depth investigations, fissure ratio (K_r), dry density (ρ_d), initial water content (w₀), and overburden stress (ln(1 + σ)) were identified as critical factors influencing expansion behavior. Experimental results revealed linear relationships between ultimate expansion (δ_ep) and w₀, ρ_d, and ln(1 + σ), and an exponential relationship with K_r. A multivariate nonlinear regression model was developed and validated, demonstrating high predictive accuracy. The model highlights the significant role of fissure infill materials, particularly gray-green clay, on soil expansiveness. It provides a reliable tool for predicting the expansion characteristics of fissured expansive soils under various conditions, offering theoretical and practical support for engineering applications in expansive soil regions. This study uses a single highly expansive clay from the Nanyang section. The soil is a transported Middle Pleistocene alluvial–proluvial clay (al-plQ2) in which fissures are predominantly filled by 2–5 mm gray-green clay. Accordingly, the proposed regression is most applicable to fissure systems that are largely infilled; extrapolation to open or partially infilled fissures should be made with caution. Full article

Given the construction industry’s significant contribution of approximately 39% of global CO₂ emissions, implementing effective carbon reduction strategies is becoming increasingly critical. In this context, Internet of Things (IoT) technologies present promising solutions for monitoring and reducing emissions. However, there is a lack of comprehensive understanding regarding specific IoT applications, implementation barriers, and opportunities for carbon reduction in construction practices. This study investigates the role of IoT in reducing carbon emissions in the construction industry. Following PRISMA guidelines, this study analyzed bibliometric data from Scopus and Web of Science databases using VOSviewer for science mapping visualization. Content analysis was conducted on 17 carefully selected articles to identify key research topics and applications. The analysis identified four mainstream application areas: (1) IoT-based smart monitoring systems for carbon emissions, (2) energy efficiency and management applications, (3) sustainable construction implementation frameworks, and (4) smart cities and other built environment applications. Key findings highlight growing research interest in IoT applications for sustainable construction, with China, the United States, and the United Kingdom leading collaborative efforts. Despite demonstrated carbon reduction potential, significant implementation barriers exist, including technical limitations, organizational resistance, skill gaps, and economic constraints. Key opportunities include Artificial Intelligence (AI) integration, Building information modeling (BIM)-IoT synergies, energy prosumer models, and standardization frameworks. This study provides the first focused review of IoT applications specifically targeting carbon reduction in construction, highlighting a critical technology-practice gap where organizational factors frequently outweigh technological barriers. A proposed socio-technical integration framework in this study bridges technical and organizational elements to overcome adoption barriers. Full article