Construction Site Research Articles

Rural Road Extraction in Xiong'an New Area of China Based on the RC-MSFNet Network Model.

High-resolution remote sensing imagery, reaching meter or sub-meter levels, provides essential data for extracting and identifying road information. However, rural roads are often narrow, elongated, and have blurred boundaries, with textures that resemble surrounding environments such as construction sites, vegetation, and farmland. These features often lead to incomplete extraction and low extraction accuracy of rural roads. To address these challenges, this study introduces the RC-MSFNet model, based on the U-Net architecture, to enhance rural road extraction performance. The RC-MSFNet model mitigates the vanishing gradient problem in deep networks by incorporating residual neural networks in the downsampling stage. In the upsampling stage, a connectivity attention mechanism is added after dual convolution layers to improve the model's ability to capture road completeness and connectivity. Additionally, the bottleneck section replaces the traditional dual convolution layers with a multi-scale fusion atrous convolution module to capture features at various scales. The study focuses on rural roads in the Xiong'an New Area, China, using high-resolution imagery from China's Gaofen-2 satellite to construct the XARoads rural road dataset. Roads were extracted from the XARoads dataset and DeepGlobe public dataset using the RC-MSFNet model and compared with some models such as U-Net, FCN, SegNet, DeeplabV3+, R-Net, and RC-Net. Experimental results showed that: (1) The proposed method achieved precision (P), intersection over union (IOU), and completeness (COM) scores of 0.8350, 0.6523, and 0.7489, respectively, for rural road extraction in Xiong'an New Area, representing precision improvements of 3.8%, 6.78%, 7.85%, 2.14%, 0.58%, and 2.53% over U-Net, FCN, SegNet, DeeplabV3+, R-Net, and RC-Net. (2) The method excelled at extracting narrow roads and muddy roads with unclear boundaries, with fewer instances of omission or false extraction, demonstrating advantages in complex rural terrain and areas with indistinct road boundaries. Accurate rural road extraction can provide valuable reference data for urban development and planning in the Xiong'an New Area.

Protecting a complex intertidal habitat in the severn estuary affected by jetty construction

This case-study presents a coastal engineering scheme that addressed a unique environmental challenge on a marine construction site. Artificially bunded reservoirs were constructed on the rocky shore of the Bristol Channel, United Kingdom, to mitigate the potential impact to ecological features of the Severn Estuary/Môr Hafren Special Area of Conservation resulting from the construction of a jetty at the Hinkley Point C construction site. The installation of piles irreversibly altered the natural supply of seawater from several large rock pools to Corallina officinalis (red seaweed) waterfalls, that the developer, EDF, was obliged to protect. Corallina can die within 30 minutes of drying out. Following rigorous topographic surveys of the foreshore, hydrodynamic modelling, and an evolution of protective measures, concrete structures were designed and installed to ensure the Corallina waterfalls were passively supplied with a constant flow of seawater throughout the tidal cycle. The artificial bunds had to be sympathetic to the natural environment while sufficiently durable to withstand the high-energy conditions of the intertidal site. A local wave buoy 13.5-year dataset shows that the scheme has withstood the two highest wave heights recorded, one of which was the third highest storm peak.

Health Risks and Improvement Measures of Construction Site Environment for Aging Construction Workers in China

Health Risks and Improvement Measures of Construction Site Environment for Aging Construction Workers in China

Optimizing Construction Management and Workflow Integration through Autonomous Robotics for Enhanced Productivity Safety and Precision on Modern Construction Sites

The construction industry is experiencing a technological transformation with the integration of robotics, fundamentally altering traditional construction management and process design. This review explores the role of construction robots in enhancing productivity, safety, and efficiency on construction sites. It examines the various types of robots used, such as bricklaying and welding robots, and analyzes their functions and real-world applications. The paper also addresses the design of workflows and processes around robots, highlighting the challenges and strategies involved in adapting construction projects to a robot-centric approach. Additionally, the impact of robotics on construction management, including shifts in roles, cost efficiency, and collaboration between humans and robots, is thoroughly explored. The review concludes by identifying future trends, challenges, and opportunities in the field of construction robotics, along with relevant policy and regulatory considerations. This paper aims to provide insights into how construction management must evolve to successfully integrate robots, leading to a more efficient, cost effective, and safe construction environment.

Construction Jobsite Image Classification Using an Edge Computing Framework

Image classification is increasingly being utilized on construction sites to automate project monitoring, driven by advancements in reality-capture technologies and artificial intelligence (AI). Deploying real-time applications remains a challenge due to the limited computing resources available on-site, particularly on remote construction sites that have limited telecommunication support or access due to high signal attenuation within a structure. To address this issue, this research proposes an efficient edge-computing-enabled image classification framework for support of real-time construction AI applications. A lightweight binary image classifier was developed using MobileNet transfer learning, followed by a quantization process to reduce model size while maintaining accuracy. A complete edge computing hardware module, including components like Raspberry Pi, Edge TPU, and battery, was assembled, and a multimodal software module (incorporating visual, textual, and audio data) was integrated into the edge computing environment to enable an intelligent image classification system. Two practical case studies involving material classification and safety detection were deployed to demonstrate the effectiveness of the proposed framework. The results demonstrated the developed prototype successfully synchronized multimodal mechanisms and achieved zero latency in differentiating materials and identifying hazardous nails without any internet connectivity. Construction managers can leverage the developed prototype to facilitate centralized management efforts without compromising accuracy or extra investment in computing resources. This research paves the way for edge “intelligence” to be enabled for future construction job sites and promote real-time human-technology interactions without the need for high-speed internet.

A method of pretreating incineration ashes containing metallic aluminium using NaOH to mitigate volume expansion under highly alkaline conditions

Globally, millions of tonnes of incineration ashes are produced with a substantial portion remaining underutilized in low-value applications or disposed in landfills. Many types of fly ashes and bottom ashes contain metallic aluminium (Al0), which causes volume expansion when the ashes are used in alkali-activated materials and as a supplementary cementitious material due to the generation of hydrogen gas at high-pH conditions. This phenomenon significantly restricts the potential applications of these ashes. To address this issue, ashes can be pretreated with NaOH to oxidize the metallic aluminium (Al0) before their utilization. This study focuses on investigating the effect of the NaOH pre-treatment duration on fly ashes from the co-combustion of recovered solid fuel, peat, and wood. A pre-treatment process was conducted using 8 mol/L aqueous NaOH solution to treat the fly ash for up to 60 minutes. The formed slurry was subsequently used to prepare alkali-activated material by mixing it with bottom ash and employing either sodium silicate or sodium carbonate as an alkali activator. The NaOH pre-treatment demonstrated a 100 % metallic aluminium conversion into oxidized form resulting enhancement in mechanical performance, microstructure, and water absorption properties. The proposed method offers a highly efficient and rapid solution for eliminating the drawbacks caused by the presence of metallic aluminium and it can be conveniently implemented on construction sites. Concurrently, this study also explores the leaching behaviour of heavy metals during alkali-activation. Significant reductions in the leaching of Ba, Cr, Cu, Mo, and Pb were observed, highlighting the environmental remediation potential of alkali-activation methods.

Automatic Planning Method of Construction Schedule under Multi-Dimensional Spatial Resource Constraints

To enhance the application of building information modeling (BIM) in schedule management for engineering projects, improve spatial planning capabilities, and minimize subjective factors in schedule preparation, this paper presents a framework and method for automatic construction schedule planning based on BIM and data-driven approaches under multi-dimensional spatial resource constraints. The method includes data acquisition, construction process reasoning, time parameter calculation, and schedule generation and scheduling. Initially, the construction data from the BIM model and manual input are imported into the reasoning system to establish the logical relationships of the construction process. Construction time parameters and spatial resource requirements are then automatically calculated using MySQL. Subsequently, the spatial layout and resource allocation data exported from the BIM model are compared to assess whether the space meets the project requirements. Finally, a construction schedule that satisfies the space constraints is generated. The method was validated through a case study, demonstrating its effectiveness in automatic schedule planning under human-computer interaction. This study introduces an innovative approach that considers spatial conflicts in the automatic scheduling process, improving planning efficiency and reducing the risk of spatial conflicts on construction sites.

Effects of Light Conditions on Tunnel Construction Workers’ Quality of Life and Work Productivity

Higher lighting intensity promotes workers’ productivity but few studies focus on the problems caused by lower lighting intensities at tunnel construction sites without natural light. The purpose of this study is to explore the relationship between light intensity and workers’ sleep quality, alertness, vitality, and work productivity through a theoretical structural equation model based on the literature review. Data were collected through a questionnaire survey, and 5792 valid responses were adopted for the analysis. First, the results showed that greater lighting intensity promoted workers’ productivity directly and indirectly through three mediators: sleep quality, alertness, and vitality. Then, the whole sample was classified into four groups: high intensity/high comfort, moderate intensity/moderate comfort, moderate intensity/low comfort, and low intensity/low comfort. The clustered results showed that the lighting conditions of tunnel construction sites were generally poor and that lighting comfort promoted workers’ productivity to some extent. Besides, the influence of lighting intensity on productivity declined with improved lighting conditions while the impact of lighting intensity on workers’ physiological and psychological status showed differing trends as lighting conditions varied. However, the relationships between workers’ physiological and psychological status and productivity remained stable regardless of the lighting conditions. The findings could provide a reference for developing corresponding measures to promote workers’ productivity.

Technological advancements and the vision of a meta smart twin city

Recent digital advancements have led the construction industry to reassess its core principles. Critical issues such as construction site impacts, aesthetics, methodologies, and sustainability are under rigorous scrutiny. The challenges hindering the digital transformation of construction remain unclear. Addressing the technical questions of when, where, why, and how the industry is evolving is crucial, especially as digital operations become more prevalent compared to traditional methods.The “digital twin” concept has emerged as a key approach in shaping the industry's future. Integrating Building Information Modelling (BIM) with the Internet of Things (IoT) has enhanced project engagement, though challenges persist. Traditionally, a digital twin represents the construction process and its interactions. But it misses the transactional and experiential aspects that integrate users into the process. Technologies like blockchain and the metaverse, combined with the digital twin, offer insights into the future of construction projects. Municipalities that adopt digital twins and metaverse representations of their commercial activities throughout construction phases are likely to set future standards for societal specifications.As some specifications such as architectural designs should be grounded in the diverse aspirations and experiences sought by citizens. This paper aims to explore the ways digital twins, smart urban environments, blockchain technology, and other reality capture datasets contribute to the vision of digital and physical construction domains. It examines the interaction and convergence of new spatial constructs, highlight the critical role of data acquisition technologies, and present a comprehensive framework for user experience and the future of Meta Smart Twin Cities.

Computer vision based early fire-detection and firefighting mobile robots oriented for onsite construction

Fires are one of the most dangerous hazards and the leading cause of death in construction sites. This paper proposes a video-based firefighting mobile robot (FFMR), which is designed to patrol the desired territory and will constantly observe for fire-related events to make sure the camera without any occlusions. Once a fire is detected, the early warning system will send sound and light signals instantly and the FFMR moves to the right place to fight the fire source using the extinguisher. To improve the accuracy and speed of fire detection, an improved YOLOv3-Tiny (namely as YOLOv3-Tiny-S) model is proposed by optimizing its network structure, introducing a Spatial Pyramid Pooling (SPP) module, and refining the multi-scale anchor mechanism. The experiments show the proposed YOLOv3-Tiny-S model based FFMR can detect a small fire target with relatively higher accuracy and faster speed under the occlusions by outdoor environment. The proposed FFMR can be helpful to disaster management systems, avoiding huge ecological and economic losses, as well as saving a lot of human lives.

Key factors affecting project delivery system selection in the Chinese construction industry

This study aims to investigate the key factors owners consider when selecting a PDS, the importance degree of these factors, and the perception differences among owners, consultants, and contractors regarding these factors. Interviews and questionnaire surveys were used to determine the importance degree of each influencing factor. And perception differences of the influencing factors on PDS among the three subjects were calculated through SPSS 15.0. The findings show that the three subjects' perceptions of the importance degree of the economic attributes of the engineering project, engineering project complexity, sub-project construction interference degree, and delivery system preference were significantly different, while the perceptions of engineering project scale, investment control requirements, schedule requirements, quality requirements, risk preference, construction management capability, land acquisition, demolition and migration, construction site conditions, local policies and regulations, and construction market development level were insignificantly different. This research can help owners understand influencing factors on PDS selection from different dimensions. Valuable information was provided for owners to select an accurate and reasonable PDS, ultimately reducing project costs and facilitating project management. Additionally, this research complements previous research on PDS selection and proposes a new influencing factors framework by exploring the key factors affecting PDS selection and the perception differences between the three subjects.

Analytical Hierarchy Process for Construction Safety Management and Resource Allocation

The construction industry plays a crucial role in contributing to the economy and developing sustainable infrastructures. However, it is known as one of the most dangerous industrial domains. Over the years, special attention has been paid to developing models for managing and planning construction safety. Many research studies have been carried out to analyze the root causes of fatal accidents in construction sites to develop models for preventing them and mitigating their consequences. Root cause identification and analysis are essential for effective risk mitigation. However, implementing mitigation activities is usually limited to the project’s safety budget. The construction sector suffers from a lack of allocation of appropriate safety resources triggered by a dynamic and complex project environment. This study aims to address the gap in safety resource allocation through a comprehensive root cause analysis of construction work accidents. In this paper, we present a comprehensive review of work accident-related research, categorized according to the 5M model into five root factors: medium, mission, man, management, and machinery. A novel methodology for construction safety resource allocation is proposed to mitigate risks analyzed by the 5M model with the aid of advanced technological solutions. Safety resource allocation alternatives are formulated, and their priorities are established based on an analysis of structured criteria that integrate both risk and cost considerations. The Analytical Hierarchy Process (AHP) is employed to select the optimal alternative for safety resource allocation, with the objective of effective risk mitigation. The proposed model underwent validation through two different case studies. The findings indicate that risk aversion is a critical factor in the optimal allocation of safety resources. Furthermore, the results suggest that regulatory measures should prioritize the stimulation of risk motivation in the safety decision-making processes of construction firms.

Assessment of the activity concentration of radon and its health hazard in surface water around the Rooppur Nuclear Power Plant (RNPP) site, Bangladesh

ABSTRACT Radon is a colourless, unscented, radioactive inert gas. As a gaseous element, Rn-222 can be effectively breathed in, leading to a health hazard. The main objective of this study is to measure the amount of Rn-222 concentration in surface water and its associated health hazards around the Rooppur Nuclear Power Plant (RNPP) construction site area in Bangladesh. Twenty water samples were collected each year (2022 and 2023) from different specific locations of the Padma River and investigated for radon concentration through a Durridge RAD7 detector with RAD H2O accessories. The range of radon activity in surface water measured from 0.070 ± 0.035 to 0.385 ± 0.211 BqL−1 with a mean activity of 0.194 ± 0.114 BqL−1 in the year 2022 and in the year 2023, the range of radon activity in surface water measured from 0.035 ± 0.070 to 0.455 ± 0.239 BqL−1 with an average activity of 0.228 ± 0.140 BqL−1. All the radon concentration results were below the recommended limits of WHO (100 BqL−1) and USEPA (11.1 BqL−1). The ranges of annual effective dose (AED) were from 0.1911 to 1.051 µSvy−1 and from 0.095 to 1.242 µSvy−1 in the years 2022 and 2023, respectively, which were lower than the AED recommended by WHO (0.1 mSvy−1). The mean values of excess lifetime cancer risk are 0.0021 × 10−3 and 0.0025 × 10−3 in the years 2022 and 2023, respectively, which were lower than the average standard value recommended by UNSCEAR (0.29 × 10−3). The result of this investigation can be applied as baseline data for radon concentration measurement in the under-construction nuclear power plant site area vicinity of Bangladesh.

Occupational exposure assessment of heavy metals among construction workers in Rawalpindi Pakistan

Construction is one of the primary drivers of development and economic activity in Pakistan. Many activities are performed at the construction site including cement mixing, carpentry, and painting. Workers working in these activities are exposed to toxic heavy metals. Due to exposure to these heavy metals, subjects are at high risk of developing diseases mainly respiratory diseases. Human hair and nail samples of construction workers in Rawalpindi, Pakistan were collected to assess the heavy metals. Heavy metals such as Al, As, Cd, Cr, Ni, K, Pb, and Zn were analyzed in the hair and fingernails of the construction workers. To determine the level of selected heavy metals, Inductively Coupled Plasma optical emission spectrometry was used. Results revealed that Al was the highest with a mean concentration of 7.54 μg/g in all three groups. Whereas Cd was below the detection limit. Heavy metal concentration was high in hair (1.77 μg/g) in two groups including cement mixing and carpentry. However, in the carpentry group heavy metal concentration was high in nails (1.19 μg/g). Additionally, the workers of the carpentry group have higher metal concentrations when compared to the other two groups and this group was at high risk of toxic metal exposure. After the correlation analysis, the results revealed that age was significantly correlated to body burden of metals (r = 0.496, p ≤ 0.05). Moreover, some of the heavy metals in hair and nails were significantly correlated with each other. Since all groups, especially carpenters, show high levels of heavy metals, there is a need for regular monitoring of heavy metals at construction sites. Most importantly, the implementation of training programs is needed to raise awareness among construction workers.

Awareness Levels of Small-Scale Contractors Regarding the Provision of Welfare Facilities on Construction Sites in Sarawak, Malaysia

Welfare facilities on construction sites are critical to ensure workers' health, safety, and well-being. However, there is a lack of studies focusing on the awareness level of welfare facilities provisions, especially those focusing on small-scale contractors (G1-G3) in Sarawak. Hence, this study explores small-scale contractors' awareness levels regarding welfare facilities in Sarawak, Malaysia. To address this issue, the researchers employed a thorough quantitative research methodology with cross-sectional descriptive analysis, delivering a well-organized questionnaire survey primarily to small-scale contractors in Sarawak. The respondents with convenience sampling were chosen from the contractor registry of the Construction Industry Development Board (CIDB), specifically from Grade 1 to Grade 3. A total of 27 questionnaires were handed out, and 283 replies were gathered. The data collected from a survey utilizing a 5-point Likert Scale were analyzed using Excel and SPSS software. The research findings show that small-scale contractors are highly aware of toilet facilities, washing facilities, changing rooms and lockers, and rest facilities. Nevertheless, they are moderately aware of the drinking water based on the mean score. Therefore, the report proposes enhanced regulatory enforcement and the establishment of focused training initiatives to enhance contractors' understanding and compliance with welfare standards, particularly with the provision of drinking water. These findings are essential for improving occupational health and safety protocols within the construction industry in Sarawak.

CALCULATION OF BEARING CAPACITY AND SUBSIDENCE OF INITIAL EMBAY IN IN REK “OSLOMEJ” - KICHEVO, R. NORTH MACEDONIA

This paper presents the geomechanical conditions for the construction of a landfill for ash and slag in REK Oslomej - Kicevo, R. North Macedonia. In this context, geotechnical investigation works and laboratory tests on the construction site, as well as the research and test methodology, are presented, and the obtained results are given in the form of appropriate graphic attachments, tabular views and diagrams. In the second part of the paper, an analysis of the geomechanical conditions for the performance of the ash and slag landfill is made, referring to the conditions for the performance of the projected initial embankments. Several aspects have been analyzed, i.e. the bearing capacity of the base constructed from tailings materials which are characterized by relatively low values of the strength and deformable parameters, forecast subsidence of the base, the possibility of underfoot sliding on the slopes of the embankments, as well as technical conditions for the construction of the embankments themselves. It should be noted that all analyzes are made with assumed values of the material to be incorporated in the embankments, which should be quantitatively and qualitatively defined after the selection of the location for the loan. However, it is appreciated that these analyzes will make their own contribution and will realistically show the expected situation during exploitation of the landfill.

Bearing Behavior of Large-Diameter Monopile Foundations of Offshore Wind Turbines in Weathered Residual Soil Seabeds

The southeastern rock base sea area is the most abundant wind resource area, and it is also the mainstream construction site of offshore wind farms (OWFs) in China. The weathered residual soil is the main seabed component in the rock base area, which is the important bearing stratum of the offshore wind turbine foundation. Previous studies on the mechanical properties of seabed materials and bearing characteristics of the pile foundations in OWFs have mainly focused on the submarine soil-based seabed, resulting in a lack of direct reference for the construction of offshore wind power in the rocky seabed. Therefore, the mechanical properties of weathered residual soil and the bearing behaviors of monopile foundations are mainly investigated in this study. Firstly, dynamic triaxial tests are conducted on the weathered residual soil, and experiments analyze insight into the evolution law of the hysteresis curve, cumulative strain, and stiffness attenuation. Then, the horizontal loading behaviors of monopile foundations in residual soil are analyzed by numerical simulations; more critically, the service performances under wind and wave coupling loads are evaluated, which provide a direct theoretical basis for the construction and design of offshore wind turbine foundations in rock base seabeds.

Computational Models of Dynamic Load Sources for Modeling of Construction Structures Operation Used in Monitoring of Technical Condition of Buildings and Structures

This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods.

‘Re-coupling site’ of social media and the workplace in digital nomadism: Chinese female workers’ self-produced vlogs with class and gender connotations

ABSTRACT We observe that a new, minor genre of resistance has emerged among female worker vloggers. Whether working in manufacturing plants or on construction sites, these female worker vloggers actively produce videos about the laughter and tears of their work lives. Their workplaces constitute the central source of their daily vlog production. We develop a concept of ‘re-coupling site’ to explore how these female vloggers transform conventional workplaces into novel digital sites, simultaneously turning themselves into digital laborers, to articulate their voices, perform their work identities, and enact their daily resistance. This concept helps induce a new interpretation of place and placed experience to fashion our understanding of working-class digital nomadism in the Global South context, where digital and cultural production can happen at work. Perhaps more importantly, the class and gender experiences articulated in their vlogs have been translated into collective practices that potentially foreground the formation of class-based online communities.

Optimized Manufacturing and Construction Site Machines Maintenance Prediction using Machine Learning and Crayfish Algorithm

Efficient maintenance prediction is critical for ensuring the operational continuity and longevity of industrial machinery. This paper presents a comparative analysis of diverse machine-learning algorithms for the task of machine maintenance prediction. Through rigorous experimentation and evaluation, we assess the performance of algorithms including AdaBoost, Random Forest, Gradient Boosting, and Support Vector Machines (SVM). Additionally, to enhance predictive accuracy, we integrate an optimizer algorithm, Cuckoo Search,into our framework. This optimization technique fine-tunes algorithm parameters, further improving accuracy. Our findings offer valuable insights into optimizing machine maintenance prediction, empowering industries with proactive maintenance strategies to mitigate downtime and enhance productivity.