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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.

One of the main issues with solid waste management is finding appropriate sites for landfill. Non-scientific and inappropriate disposal practices have a negative impact on the environment which affects the quality of life. The study provides an integrated framework with a focus on structuring the decision-making process for the landfill suitability site map. This could be determined by the use of proper data collection, criterion weighting and normalization. In order to understand the procedures that affect the suitability of landfill sites, the integrated GIS-based fuzzy-AHP-MCDA method was implemented to appropriate landfill site for Abha-Khamis-Mushyet located in Aseer region Following the extensive literature review and expert opinion, 10 themes were selected for this study such as drainage density, land use/land cover (LULC), slope, elevation, lineament density, normalized difference vegetation index (NDVI), rainfall, distance from the airport, distance from road, and geology. These themes have been developed through RS (remote sensing) and conventional data. Subsequently, potential landfill sites were identified and divided into five classes: very low suitable (fuzzy value 0.20–0.45), low suitable (0.46–0.55), moderately suitable (0.56–0.65), high suitable (0.66–0.75), and very high suitable (0.76–0.92). According to the statistical analysis, 23.91% and 3.67% of the total area were within a very good and good landfill area, while 38.14% and 22.84% accounted for the moderate and poor suitable zone, respectively. As a quality-based site, the existing two landfill sites were located over a very low suitable and low suitable potential area while one landfill site was located over the high suitable∙ The spatial variance of high and very high potential landfill site zones found in the north-eastern, east-central and south-eastern parts of the watershed. The sensitivity analysis was performed to determine the efficacy of each parameter and reveals that the effective weights for each theme differ slightly from the theoretical weight assigned to the landfill site suitability zone. This technique and its findings can provide an appropriate guideline to assist hydrogeologists, engineers, regional planners, and decision-makers in selecting an optimal landfill site in the future.

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 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.