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Artificial Neural Networks (ANNs), the most popular and widely used Artificial Intelligence (AI) technology due to their proven accuracy and efficiency in control, estimation, optimization, decision making, forecasting, and many other applications, can be employed to achieve faster sustainable development of construction industry. The study presents state-of-the-art applications of ANNs to promote sustainability in the construction industry under three aspects of sustainable development, namely, environmental, economic, and social. The environmental aspect surveys ANNs’ applications in sustainable construction materials, energy management, material testing and control, infrastructure analysis and design, sustainable construction management, infrastructure functional performance, and sustainable maintenance management. The economic aspect covers financial management and construction productivity through ANN applications. The social aspect reviews society and human values and health and safety issues in the construction industry. The study demonstrates the wide range of interdisciplinary applications of ANN methods to support the sustainable development of the construction industry. It can be concluded that a holistic research approach with comprehensive input data from various phases of construction and segments of the construction industry is needed for the sustainable development of the construction industry. Further research is certainly needed to reduce the dependency of ANN applications on the input dataset. Research is also needed to apply ANNs in construction management, life cycle assessment of construction projects, and social aspects in relation to sustainability concerns of the construction industry.

The Normalized Difference Vegetation Index (NDVI) and rainfall data were used to model the spatial relationship between vegetation and rainfall. Their correlation in previous studies was typically based on a global regression model, which assumed that the correlation was constant across space. The NDVI–rainfall association, on the other hand, is spatially non-stationary, non-linear, scale-dependent, and influenced by local factors (e.g., soil background). In this study, two statistical methods are used in the modeling, i.e., traditional ordinary least squares (OLS) regression and geographically weighted regression (GWR), to evaluate the NDVI–rainfall relationship. The GWR was implemented annually in the growing seasons of 2000 and 2016, using climate data (Normalized Vegetation Difference Index and rainfall). The NDVI–rainfall relationship in the studied Bisha watershed (an eco-sensitive zone with a complex landscape) was found to have a stable operating scale of around 12 km. The findings support the hypothesis that the OLS model’s average impression could not accurately represent local conditions. By addressing spatial non-stationarity, the GWR approach greatly improves the model’s accuracy and predictive ability. In analyzing the relationship between NDVI patterns and rainfall, our research has shown that GWR outperforms a global OLS model. This superiority stems primarily from the consideration of the relationship’s spatial variance across the study area. Global regression techniques such as OLS can overlook local details, implying that a large portion of the variance in NDVI is unexplained. It appears that rainfall is the most significant factor in deciding the distribution of vegetation in these regions. Furthermore, rainfall had weak relationships with areas predominantly located around wetlands, suggesting the need for additional factors to describe NDVI variations. The GWR method performed better in terms of accuracy, predictive power, and reduced residual autocorrelation. Thus, GWR is recommended as an explanatory and exploratory technique when relations between variables are subject to spatial variability. Since the GWR is a local form of spatial analysis that aligned to local conditions, it has the potential for more accurate prediction, however, a larger amount of data is needed to allow a reliable local fitting.

Groundwater is a valuable resource because it is widely used for drinking, and for domestic, agricultural, and industrial purposes. Globally, Saudi Arabia is known to be one of the driest regions with scarce water resources. The shallow groundwater near the major cities in the Kingdom of Saudi Arabia is becoming polluted because of industrial effluent discharge, use of fertilizers in agriculture and domestic sewerage in the region. This review tries to focus on groundwater quality problems due to anthropogenic or geogenic sources in the region of Saudi Arabia. In this paper, we focus on different water-quality variables, for groundwater quality evaluation and aquifer vulnerability assessment due to pollutants/contaminants present in groundwater. The current study gives a holistic understanding of different groundwater quality problems and therefore identifies the gaps of the previous studies and identifies the viewpoints of the future research dimensions. We describe the different groundwater quality problems related to toxicities of the fluoride, nitrate, and heavy metals and radionuclides in Saudi Arabia. A majority of the groundwater pollutants are of natural origin, but there is significant wastewater effluent discharge in the region that is also responsible for contamination of aquifers with heavy metals.

The penetration to geological shield occurs in many situations at various velocities and scales, for example, meteor-cratering, pile driving, falling of objects from high-rise building construction, and debris/fragments from failed components. The soil media is an efficient energy dissipation system and effective shock protection shield. Impact circumstances are currently getting widespread attention. A lot of research has been done on soil media for impact and penetration. The phenomenon of dynamic penetration in heterogeneous particulate soil medium is very complex and the target soil media under dynamic impact especially under high speed and deep penetration neither behave completely as solid nor as liquid. The topics of recent research interest in the field of penetration to soil media and their significant findings are critically reviewed in the present study. The dedicated review of analytical, empirical, experimental, and computational methods to predict the response of soils media-impacting objects to penetration is presented. The emerging challenges in fundamental research of penetration into soil media are outlined and it is an attempt to formulate the future research directions in the field of soil media penetration.

This study focused on the areas of Petaling Street and Jalan Hang Kasturi, Kuala Lumpur, in a historical enclave that is well known locally for its cultural, architectural, and historical interest that is worth preserving and conserving. To fulfill the purpose of enhancing the areas, the local authority introduced a covered pedestrian street, which is said to be more convenient for shoppers, considering the tropical climate of Kuala Lumpur. This effort is believed to have been done without any consultation with heritage conservators and activists, thus invoking a debate regarding its many pros and cons. This study examined the arguments concerning the intervention in the heritage area from various groups of stakeholders that are directly involved. Furthermore, this paper presents the method of implementation used by the local authority when executing a conservation project. The collection of primary and secondary data in the form of surveys and interviews with the professionals, traders, and officials in the local area was carried out. The findings show that the majority of the respondents had no objection to the modern intervention in the Heritage Enclave, including the roofing structure, except for its design. This study also found that the intervention did not affect the heritage value of the place, but at the same time, brought concerns regarding the extemporaneous method taken by the local authority when implementing the project.

The rapid economic growth of Saudi cities after the discovery of oil in 1960 had some disadvantages, the most significant of which was the rapid search for alternatives to urban development and the acceleration of urban growth in its major cities and villages. That contributed to the implementation of certain planning policies based on the heavy use of large-scale vehicles. These policies have been instrumental in increasing horizontal expansion, which has been linked to the increased need to rely on cars as a means of movement and not to adopt public transport such as metro and railways. In this research, one of the main cities in the Asir region, which is the administrative capital of Abha, which has been evaluated and analyzed. Space syntax is an informative theory that stands on the structure of urban graphs. Utilizing syntactic analysis, the impact of highways and arterial roads on the integration and connectivity orientation in the urban structure of the city is analyzed, and the constraints and opportunities for development in the building use map are identified. Resulting in isolated parts of districts with no pedestrian routes to connect them, this methodology allows us to determine the main points in the structure of the city where pedestrian accessibility can be added in order to provide the remedy to overcome the shortage in the city&rsquo, s network system (i.e., crossovers, tunnels, etc.). In addition, the impact on the human dimension of the living community, the diversity of land use, and real estate financial classifications were discussed, while the principles of sustainable planning were used to enhance the integration of walkability in the built environment, which was the goal of this study.

The dam is a crucial water source for both consumption and irrigation in the Asir region of the Kingdom of Saudi Arabia. The current study evaluates surface water quality at the dam and examines the effects of some physicochemical and trace metals on irrigation using multiple statistical approaches. The physicochemical parameters and trace metals of the dam water were measured at 27 sites in the Asir region. Three sites were generated using the K-mean clustering technique; the first group included five sites, the second group contained 20 sites, and the third group added 2 sites. The chemical facies of the surface water were Na-K-SO42−. The surface water had low levels of Zn (0.19 mg/L), Cd (0.10 mg/L) and Pb (0.22 mg/L) except for B (38.50 mg/L), excessive concentrations of Na (2090.65 mg/L), K (535.72 mg/L), SO42− (208.11 mg/L) and Cl− (105.96 mg/L), while pH varied between 6.0 and 8.5 except at a few sites. The EC (electrical conductivity) values were within the standard for irrigation purposes. The results of irrigation water indices such as magnesium absorption ratio (MAR), magnesium hazard (MH), Kelly’s ratio (KR), and soluble sodium percentage (SSP) indicate that dam water is mostly fit for irrigation except for sodium percentage (Na%) and sodium adsorption ratio (SAR). The irrigation water quality index (IWQI) values revealed that 51.85% of samples had a high suitability class and 11.11% of samples had moderate suitability, whereas the rest were low suitability for irrigation use. The redundancy analysis (RDA) biplot revealed that water pH, DO, TH, and SO42− were increased with decreased EC and salt level. The generalized linear model (GLM) model found that salt had a negative effect on the amount of Fe, Ni, Se, and Al concentrations. The study recommends that proper protective measures, including acceptable criteria for different water parameters, are required to reduce the potential influence of physicochemical parameters and metals on irrigation water in agricultural fields.

The site selection process for a building entails evaluating a variety of factors with varying degrees of importance or percentage influence. In order to ensure that critical site selection factors are not overlooked, a methodology for calculating a building’s safe site selection must be developed. The study identified three broad aspects widely considered in site selection, namely environmental, physical, and socioeconomic criteria. To assess the safest site selection of residential building construction for sustainable urban growth, we used GIS-based multi-criteria decision-making approach that combined Fuzzy-AHP and weighted linear combination (WLC) aggregation method used to calculate the SSPZ. The final safe site suitability map was generated by aggregating all aspects such as geophysical, socio-economic and Geo-environmental thematic layers and their associated Fuzzy-AHP weights using the weighted linear combination method. The sites potential index’s mean value of 0.513 with standard deviation of 0.340, minimum and maximum GeoPhySSSI are 0.0 and 0.91, respectively, SSS index is classified into zones by histogram profile using natural breaks (jenks)” Subsequently, safe sites identified and divided into six classes namely no construction, very low suitable site low suitable site, moderate suitable site, high suitable site, and very high suitable site.“ According to the statistical analysis, 3.64% and 32.12% of the total area were under very high and high SSSZ, while 26.40% and 6.22% accounted to the moderate and low suitable potential, respectively” Our findings suggest that integrating the fuzzy collection with AHP is highly desirable in terms of alternative and decision-making effectiveness. The study reveals that the areas of high and moderate suitability are located near existing habitant area, major roads, and educational and health services; they are not located in restricted/protected areas or are vulnerable to natural hazards. The findings indicate that unsuitable and less-suitable land uses such as vegetation, protected areas, and agriculture lands cover nearly one-third area of Abha-Khamis Mushyet regions, implying that using Fuzzy-AHP and GIS techniques will significantly aid in the conservation of the environment. This would significantly mitigate adverse effects on the ecosystem and climate.

Bangladesh is one of the most climate-vulnerable countries on the globe. The country is frequently affected by numerous climatic events including floods, droughts, cyclones, etc., which damages the farm household’s livelihood and socio-economic condition. Therefore, this work intends to appraise the smallholder farmers’ perceived climate-related risk, impact, and the factors that influence their choices of adaptation strategies to cope with the adverse impact of the climatic extreme events in northern Bangladesh. Survey data were collected from 300 respondents from two drought-prone districts of northern Bangladesh in January–February 2020. The climate-related risk perception index (CRRPI) was constructed to assess the farmers’ perceived risk. The multinominal logit (MNL) model was employed to explore the factors influencing farmers’ choices of adaptation strategies. Farmers’ perceptions of climate change risk were found to be consistent with meteorological data in the research area. Results of the CRRPI revealed that flood, drought, riverbank erosion, and heat waves were the critical risks perceived by the farmers. Farmers used a variety of adaptation measures to deal with these climatic threats, including agricultural diversification, changes in fertilizer and insecticides, and crop and seed changes. The MNL model results showed that the factors that influenced a farmer’s choices of adaptation strategies were age, education level, family members, income level, year of farming experience, and the farmer’s information on climate change. This study also demonstrated that water scarcity in the dry period and the frequency of crop diseases were the major limiting factors experienced by the farmers whilst undertaking adaptation strategies. Thus, awareness and capacity building through training and support to adopt the adaptation strategies are essential to enhance the resilience of the farmers.

The development of a concrete mixture design process for high-quality concrete production with sustainable values is a complex process because of the multiple required properties at the green/hardened state of concrete and the interdependency of concrete mixture parameters. A new multicriteria decision making (MCDM) technique based on Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methodology is applied to a fuzzy setting for the selection of concrete mix factors and concrete mixture design methods with the aim towards sustainable concrete quality management. Three objective properties for sustainable quality concrete are adopted as criteria in the proposed MCDM model. The seven most dominant concrete mixture parameters with consideration to sustainable concrete quality issues, i.e., environmental (density, durability) and socioeconomic criteria (cost, optimum mixture ingredients ratios), are proposed as sub-criteria. Three mixture design techniques that have potentiality to include sustainable aspects in their design procedure, two advanced and one conventional concrete mixture design method, are taken as alternatives in the MCDM model. The proposed selection support framework may be utilized in updating concrete design methods for sustainability and in deciding the most dominant concrete mix factors that can provide sustainable quality management in concrete production as well as in concrete construction. The concrete mix factors found to be most influential to produce sustainable concrete quality include the water/cement ratio and density. The outcomes of the proposed MCDM model of fuzzy TOPSIS are consistent with the published literature and theory. The DOE method was found to be more suitable in sustainable concrete quality management considering its applicable objective quality properties and concrete mix factors.

Saudi Arabia&rsquo, s arid and semi-arid regions suffer from water scarcity because of climatic constraints and rapid growth of domestic and industrial water uses. The growing demand for high-quality water supplies and to reduce the dependency on desalination creates an urgent need to explore groundwater resources as an alternative. The weighted overlay analysis method using the fuzzy-analytical hierarchy process (FAHP) multi-criteria decision making (MCDM) techniques combined with geoinformation technology was used in this study to explore the groundwater potential zones in the Itwad-Khamis watershed of Saudi Arabia. Twelve thematic layers were prepared and processed in a GIS setting to produce the groundwater potential zone map (GPZM). Subsequently, potential groundwater areas were delineated and drawn into five classes: very good potential, good potential, moderate potential, poor potential, and very poor potential. The estimated GWPZ (groundwater potential zones) was validated by analyzing the existing open wells distribution and the yield data of selected wells within the studied watershed. With this quality-based zoning, it was found that 82% of existing wells were located in a very good and good potential area. The statistical analysis showed that 14.6% and 28.8% of the total area were under very good and good, while 27.3% and 20.2% were accounted for the moderate and poor potential zone, respectively. To achieve sustainable groundwater management in the Aseer region, Saudi Arabia, this research provided a primary estimate and significant insights for local water managers and authorities by providing groundwater potential zone map.

Saudi Arabia is an arid country with very limited water resources. The absence of surface water bodies along with erratic rainfall renders groundwater as the most reliable source of potable water in arid and semi-arid regions globally. Groundwater quality is determined by aquifer characteristics regional geology and it is extensively influenced by both natural and anthropogenic activities. In the recent past, several methodologies have been adopted to analyze the quality of groundwater and associated hydro-geochemical process i.e., multivariate statistical analysis, geochemical modelling, stable isotopes, a redox indicator, structural equation modelling. In the current study, statistical methods combined with geochemical modelling and conventional plots have been used to investigate groundwater and related geochemical processes in the Aseer region of Saudi Arabia. A total of 62 groundwater samples has been collected and analyzed in laboratory for major cations and anions. Groundwater in the study region is mostly alkaline with electrical conductivity ranging from 285&ndash, 3796 &mu, S/cm. The hydro-geochemical characteristics of groundwater are highly influenced by extreme evaporation. Climatic conditions combined with low rainfall and high temperature have resulted in a highly alkaline aquifer environment. Principal component analysis (PCA) yielded principal components explaining 79.9% of the variance in the dataset. PCA indicates ion exchange, soil mineralization, dissolution of carbonates and halite are the major processes governing the groundwater geochemistry. Groundwater in this region is oversaturated with calcite and dolomite while undersaturated with gypsum and halite which suggests dissolution of gypsum and halite as major process resulting into high chloride in groundwater. The study concludes that the combined approach of a multivariate statistical technique, conventional plots and geochemical modelling is effective in determining the factors controlling the groundwater quality.