Ensuring occupational safety and health (OSH) is paramount in infrastructure projects due to their inherently high-risk nature and the increased likelihood of accidents. Despite its importance, numerous obstacles impede the successful adoption of OSH measures in these settings. Addressing these challenges is key to not only implementing OSH protocols effectively but also to improving working conditions and managing other operational facets like quality and environmental concerns, ultimately resulting in better infrastructure developments. Adopting proactive OSH strategies is crucial for preventing significant accidents and fostering a safety culture within infrastructure projects. This review focuses on identifying the primary obstacles and barriers to effective OSH in infrastructure projects, laying the groundwork for improving safety performance in the sector. It highlights organizational and legislative issues as the foremost challenges due to their direct impact on safety culture, resource distribution, compliance, and accountability. Although factors related to environmental and safety practices are deemed less critical, they are nonetheless vital for comprehensive risk management and the promotion of a safe working environment. Tackling these issues is imperative for cultivating a strong safety culture and safeguarding the health of workers on infrastructure projects. It is also essential to acknowledge the distinct OSH challenges presented by different construction scenarios to devise customized safety measures and effectively reduce risks. This review emphasizes the necessity of recognizing the unique aspects of each construction project, addressing specific dangers, and meeting regulatory demands to achieve thorough safety management.

The three categories of energy scarcity, population growth and environmental concerns explain the need for new energy sources. Saudi Arabia has become one of the regions capable of using solar energy, particularly through the use of photovoltaic systems, thanks to Saudi Arabia’s excellent ability to effectively utilize the sunlight. This study examines the performance of photovoltaic-integrated shading systems (PVIS) in enhancing energy efficiency for residential buildings under the extreme climatic conditions of Riyadh and Abha in Saudi Arabia. The study advances the knowledge of PVIS applications by addressing the dual challenges of energy efficiency and sustainability in urban residential settings. Leveraging numerical simulations conducted with EnergyPlus, the research evaluates various shading configurations, including louvers, horizontal and sidefin canopies, to quantify their impact on cooling, heating, lighting demands and energy production. The annual efficiency of the proposed integrated systems to achieve sustainable and net-zero energy buildings (NZEBs) is a key metric evaluated in this study. The key findings highlight the effectiveness of horizontal PVIS in achieving the highest energy efficiency, with up to 27.19% in Abha and 24.72% in Riyadh, based on the ratio of annual available solar energy to PV energy production. The integration of PVIS not only reduces the cooling loads by optimizing shading but also contributes significantly to renewable energy production toward NZEBs. The lifecycle cost analysis (LCCA) identifies horizontal canopies as the most cost-effective configuration, with a payback period of 8.6 years in Abha and 10.2 years in Riyadh.

Tunnel construction projects are complex engineering projects that pose numerous safety challenges. Accordingly, prioritizing the protection of workers, the public, and the environment is imperative. This study aimed to comprehensively analyze the most significant risks associated with tunnel construction projects in Saudi Arabia. Twenty-nine hazards were identified through site inspections and interviews with engineers and managers engaged in various tunnel projects in Saudi Arabia. These risks were categorized into six groups, namely, Confined Spaces, Air surveillance & ventilation, Fires, Physical and chemical hazards, Electricity, and Personal safety and emergency plans. Data were acquired from 108 respondents completing a questionnaire. The data were statistically analyzed using the SPSS V20 package. The Total Importance Index Impact (TIII) application determined the most crucial risks affecting tunnel construction safety management. As a result, the most significant risk identified are Musculoskeletal disorder due to heavy manual handling, prolonged use of hand tools, or standing, Oxygen shortage brought on by the narrow tunnel, and Constant exposure to high noise; are the most effecting risks. The findings demonstrate that risk analysis facilitates project managers in identifying and focusing on principal risks, which supports the implementation and evaluation of safety management plans. By providing practical guidelines, risk analysis enhances the success rate of tunnel construction projects. Implementing measures to mitigate exposure to elevated noise levels, air supply hazards, fires, and oxygen deficiency is anticipated to result in numerous benefits, including improved worker health and performance, reduced time and expenses, enhanced productivity, and an improved reputation among staff and clients.

Building maintenance and operation costs represent a significant portion of the life cycle costs (LCC) of construction projects. The accurate estimation of these costs is essential for ensuring the long-term sustainability and financial efficiency of buildings. This study aims to develop a novel framework for predicting maintenance and operation costs in construction projects by integrating an emotional artificial neural network (EANN). Unlike traditional models that rely on linear regression or static machine learning, the EANN dynamically adapts its learning through synthetic emotional feedback mechanisms and advanced optimization techniques. The research collected input data from 313 experts in the field of building management and construction in Ha’il, Saudi Arabia, through a comprehensive questionnaire. The integration of expert opinions with advanced machine learning techniques contributes to the innovative approach, providing more reliable and adaptive cost predictions. The proposed EANN model was then compared with a classic artificial neural network (ANN) model to evaluate its performance. The results indicate that the EANN model achieved an R² value of 0.85 in training and 0.81 in testing for buildings aged 0 to 10 years, significantly outperforming the ANN model, which achieved R² values of 0.78 and 0.72, respectively. Additionally, the Root Mean Squared Error (RMSE) for the EANN model was 1.57 in training and 1.60 in testing, lower than the ANN’s RMSE values of 1.82 and 1.90. These findings show that the superior capability of the EANN model in estimating maintenance and operation costs.. This led to more accurate long-term maintenance cost projections, reduced budgeting uncertainty, and enhanced decision-making reliability for building managers.

Although extensive research has been conducted to explain the high accident rates in the Indian construction industry, studies focusing on the contributions of the prevailing safety climate as an enabler of such incidences remain sparse. Safety climate plays a crucial role in shaping workers’ safety behaviors. Therefore, eliciting the perspectives of construction workers concerning safety climate dimensions that are critical for engendering improved safety behavior will provide valuable insights into the dimensions required to sustain the desired safety performance levels on construction sites. This study adopted a sequential mixed-methods research design. Purposively selected respondents and interviewees were surveyed and interviewed at various intervals. The study established that safety climate dimensions, such as effective leadership, effective communication, consultation, training, resources, incentives, and recognition, are critical in improving safety behavior among construction workers. The results of this study have significant implications for practice and knowledge, as they provide an approach for assessing the impact of different safety climate dimensions on the safety behavior of construction workers in India. Understanding these dimensions will lead to a framework for managing these challenges and improving construction safety performance. The study reported in this paper remains one of the few studies seeking to explore the impact of safety-climate dimensions on worker safety behavior in the construction industry.

Poor sleep and related sleep disorders have been linked to subpar performance in sectors like health and education. Such sleep issues in the workforce negatively affect individual and organisational productivity. Despite this, the high-stress environment of the construction sector has been largely overlooked. This study delves into the role of sleep in construction field management and human resource practices, examining how a better understanding of workers' sleep patterns could enhance job performance. The research involved an online survey of 119 construction workers in the city of Jeddah in Saudi Arabia, focusing on their sleep duration and its impact on job performance, with data analysis conducted using SPSS software. The findings indicate that inadequate sleep influenced by factors such as dietary habits is significantly related to poor performance. The majority of workers are affected by poor sleep quality. The study suggests that construction management should implement health awareness campaigns to improve workers' responsiveness and awareness regarding sleep. It emphasises the need for management to develop strategies to increase sleep awareness and education in the construction industry, aiming to improve overall job performance.