Abdul Salam Darwish

This study investigates the potential of using deep learning for real-time image analysis in assessing sustainable infrastructure and urban development. Convolutional Neural Networks (CNNs) are implemented to evaluate live-captured building images, enabling automated classification and data extraction for decision-making. The proposed approach overcomes the limitations of existing methods by facilitating real-time analysis and large-scale data processing. A dataset exceeding 12,000 images rigorously evaluates the CNN model's performance. This research establishes a framework for leveraging deep learning for real-time assessment of sustainable infrastructure, paving the way for improved data-driven urban planning and development decision-making. The study confirms that the Inception Net V3-based feature extraction technique accurately classifies images based on CO2 emission levels. This classification task is best performed using the Neural Network model. Advanced feature extraction techniques are essential for improved environmental image classification.

Initiation of heat energy absorb, and release depends on the surrounding temperature and phase transition temperature of PCM. Nevertheless, the commonly hindered practical issue of PCMs is poor optical absorbance, fluctuation in energy storage and low thermal conductance. The current research aimed to assess the chemical constancy, improve the optical absorbance, decrease the optical transmittance & to analyse the variation in melting enthalpy of organic PCM functioning at 50 degrees C via dispersion of coconut shell biochar-based carbon micro particles (CSCMPs). The synthesized CSCMPs are dispersed within the PCM matrix at weight fraction of 0.2%, 0.4%, 0.6%, 0.8% and 1.0% via meltingblending-sonication process. The developed composite organic PCMs are analysed with a series of material characterization experiments by employing Fourier Transform Infra-Red spectroscopy (FTIR), Ultraviolet visible spectroscopy (UV-Vis), and differential scanning calorimeter (DSC). Results ensure, chemical stability, improved optical absorbance by 63.6%, decreased optical transmissibility by 64.3%; and surge in energy storage ability from 158.2 J/g to 190.1 J/g. The findings also provide valuables information towards design and improvement of composite PCM materials for various thermal regulation application from buildings to electronic devices.

Landfills have significant environmental and social impacts due to their associated greenhouse gases (GHGs) emissions. This paper examines solid waste management using Ajman-United Arab Emirates as a case study. It emphasises the necessity of having waste assessment integrated with air quality assessment to monitor and regulate waste disposal procedures The paper examines waste accumulation, previous treatments & services provided at the Ajman landfill. Forecasts of waste accumulated at the landfill indicate a serious issue that needs immediate action from Ajman Municipality despite the low percentage of treatments currently performed. It was found that GHGs increased between 2017 and 2023, with a decrease in 2020 due to COVID-19. Additionally, the paper proposes an integrated waste management model that can reduce landfill-associated GHG emissions and their negative impact on the environment. Moreover, the research predicted that by 2035, Ajman will be able to handle 250,000 tons of waste per year. Moreover, it was indicated that Ajman's environmental trajectory can be improved significantly by capping the landfill.

Carbon reduction initiatives cannot be implemented unless and until, main workplace processes have been dealt with to similar standards. This study critically evaluates the strategic implementation of environmental management systems in the United Arab Emirates (UAE) construction industry and their contribution to zero carbon goals. As part of robust management systems, it is argued that generic best practice simultaneously promotes optimum outcomes in both - they are mutual and not independent of each other. The study adopted a quantitative research method approach. A questionnaire survey was conducted, with responses from 106 UAE construction professionals. There is emphasis in the research on the value of soft-systems research methodologies (non-technical) as a tool to investigate environmental problems rather than scientific or technical approaches. The findings indicate that reviews, audits, and evaluations are essential for projects to sustain their specialist competence. These mechanisms assist project managers in navigating the evolving landscape of industry by leveraging accumulated expertise. Common challenges include a lack of clarity and executing tasks in an unordered manner, which can impede construction involves refining operations and side-stepping mistakes. Technical and nonand zero carbon outcomes.

This study critically evaluates the strategic implementation of environmental management systems in the United Arab Emirates (UAE) construction industry and their contribution to zero carbon goals. As part of robust management systems, it is argued that generic best practice simultaneously promotes optimum outcomes in both-they are mutual and not independent of each other. The study adopted a quantitative research method approach. A questionnaire survey was conducted, with responses from 106 UAE construction professionals. There is emphasis in the research on the value of soft-systems research methodologies (non-technical) as a tool to investigate environmental problems rather than scientific or technical approaches. The findings indicate that reviews, audits and evaluations are essential for projects to sustain their specialist competence. These mechanisms assist project managers in navigating the evolving landscape of industry by leveraging accumulated expertise. Common challenges include a lack of clarity and executing tasks in an unordered manner, which can impede excellence involves refining operations and side-stepping mistakes. Technical environmental and zero carbon outcomes.

In recent years, significant attention has been paid to the use of Artificial Neural Network (ANN) techniques in the construction sector due to their ability to handle big data, predict risks, results accuracy, make reliable assessments, and solve complex nonlinear problems. This paper introduces a comprehensive sustainable methodology for risk assessment that is supported by artificial intelligence (AI). The methodology consists of four phases; phases one and two determine the risk factors impacting sustainable construction (SC) by collecting data from projects in Iraq (phase one) and conducting semi-structured interviews (phase two). Phase three applies a Failure Mode and Effect Analysis method to identify the risk factor values and apply an ANN model. Phase 4 uses the Absolute Percentage Deviation method to verify the proposed model. The study findings indicate that the ANN-based model provides more accurate and reliable risk assessments for SC projects than traditional methods. The model effectively integrates and analyses multiple variables and factors across the project life cycle, providing a comprehensive and dynamic view of risks and their potential impact.

A Floating Wind-H2 System can support efforts toward a net-zero future through its synergistic potential. This paper overviews the powerful synergy between floating wind and hydrogen technologies. Floating wind technology has made significant advances in terms of turbine size and efficiency, opening a vast offshore wind resource. H2's multifaceted advantages and the trajectory of these systems within the broader energy landscape are analysed in a multidimensional approach to assessing their transformative potential. Floating Wind-H2 Systems are examined, revealing current and prospects based on existing projects. As floating wind technology evolves, they shed light on H2's nuanced role in the energy transition and provide insights into the feasibility and impact of integrating these technologies at scale. Using Ajman, UAE, as a case study to illustrate regional adaptation, this paper discusses the significance of floating wind and hydrogen technologies for achieving global net-zero targets. The comparison of centralised onshore and decentralised offshore electrolysis demonstrated the importance of flexible solutions, particularly in regions like Ajman with limited land availability. An innovative approach to clean energy infrastructure is demonstrated by the proposed wind-H2 system in Ajman, which relocates offshore facilities to overcome land constraints, reduce costs, and facilitate free trade. The system can produce more than 5 Tons of H2 per day considering power generation of 3.4 MW per wind turbine for 3 turbines.

Pollution can originate from fixed, mobile, and local sources, due to human activity or naturally occurring processes. The well-developed cities contribute to over 70% of global carbon emissions. This paper analyses the parameters that contribute to achieving healthy, environmentally sustainable cities. A strategic planning framework is introduced to implement efficient and effective strategies for future sustainable cities. Therefore, the paper aims to identify and examine successful factors within a framework to reduce negative environmental impacts from air pollution designed for future sustainable cities. Data is collected from locations that reflect the nature of human settlement and well-being, and Advanced SWOT analysis was conducted to see the success factors. Data analyses reveal many factors that must be monitored to achieve SDG 11 targets. The results show how air quality affects people's health and social living conditions in urbanised areas. Comparisons between pre-and-post Covid 19 indicated the impact of the pandemic on air quality and showed evidence of possible reductions in air pollution when activities are reduced. The method used for this research is analysing the data recorded from a network of environmental stations constructed at different sites in the Emirate of Ajman. The achieved framework consists of strategies categorised into five main categories, formed by different functional layers, to demonstrate actions needed by the government. Recommendations have been drawn from the findings, and if considered, it could be possible to achieve sustainable air quality. Keywords: Aerodynamics, Forebody and afterbody, Next keyword, Projectile, Supersonic speed.

Risk Assessments in construction projects help in cost savings, energy efficiency, as well as on time completion within the allocated budget. To meet these requirements, companies need to use analytical models that save time, deal with large amounts of data, and allow them to make better decisions more quickly. In addition, it will facilitate a fast, accurate, and automated process. This paper aims to provide a comprehensive critical analysis of traditional and AI -based risk assessment frameworks for sustainable construction projects (SCP) and the most practical framework. In this respect, the paper reviewed the literature and conducted semistructured interviews on risk assessment and its application in construction projects. It also explored the advantages and disadvantages of traditional and AI -based risk assessments. A case study of modern sustainable construction projects in a selected country (Iraq) was undertaken to assess risk factors associated with these projects. An Analytical Hierarchy Process (AHP) and Artificial Neural Network (ANNs) approaches were used to reveal the variation of results between traditional and AIbased risk assessment regarding accuracy, reliability, and cost-effectiveness. An independent sample t -test was calculated to verify the differences in the results obtained by the AHP and the ANN methods. The findings show the advantages and disadvantages of traditional and advanced risk assessment in sustainable construction projects and establish recommendations for optimum practice in risk assessment methodologies. Also, the findings indicate that the value of the t -test was 0.7415, which is greater than 0.05; this means there is no substantial difference in the results of assessing the risk factors that impact sustainable construction projects if AHP or ANNs methods are used. The paper concludes that while traditional frameworks are still prevalent in the construction industry, advanced techniques can improve accuracy, reliability, and cost-effectiveness. The implications for sustainable construction practice and policy and identifies future research directions.

Smart sustainable cities rely on the latest technologies and apply recent knowledge like Information and Communication Technologies (ICT), BIM, and lean construction to expand people's eminence of life, smooth urban maneuvers and facilities more competent, and develop their competitiveness while confirming that they achieve the economic, social, environmental, and cultural demands of current and forthcoming generations. This paper explores the synergies between Building Information Modelling (BIM) visualisation and Lean construction practices to enhance Architecture, Engineering, and Construction (AEC) industry performance. A structured questionnaire was distributed among BIM and lean experts and analysed by SPSS. The study uses descriptive and correlation analyses to assess ten key lean practices, revealing high industry adoption and favorable mean scores. Notably, BIM-enhanced clash detection and coordination lead with a score of 4.4 out of 5. Correlation analysis establishes significant positive associations between BIM visualisation and practices such as just-in-time production, value stream mapping, lean pull systems, work sequencing, standardised work, and continuous improvement. The findings accentuate the pivotal role of BIM in optimising lean practices, offering valuable insights for practitioners seeking to elevate AEC industry performance through strategic integration. Future studies endeavors are recommended to investigate several alternative avenues to enhance the integration between BIM and Lean practices in the AEC industry. Furthermore, the forthcoming researchers are advised to validate the proposed framework