Building performance prediction is a significant area of research, due to its potential to enhance the efficiency of building energy management systems. Its importance is particularly evident when such predictions are validated against field data. This paper presents an intelligent computational model combining Monte Carlo analysis, Energy Plus, and an artificial neural network (ANN) to refine energy consumption and thermal comfort predictions. This model addresses various combinations of architectural building design parameters and their distributions, effectively managing the complex non-linear relationships between the response variables and predictors. The model’s strength is demonstrated through its alignment with R² values exceeding 0.97 for both thermal discomfort hours and energy consumption during the training and testing phases. Validation with field investigation data further confirms its accuracy, demonstrating average relative errors below 2.0% for total energy consumption and below 1.0% for average thermal discomfort hours. In particular, an average underestimation of −12.5% in performance discrepancies is observed when comparing the building energy simulation model with field data, while the intelligent computational model presented a smaller overestimation error (of +8.65%) when validated against the field data. This discrepancy highlights the model’s potential and reliability for the simulation of real-world building performance metrics, marking it as a valuable tool for practitioners and researchers in the field of building sustainability.

Water scarcity and energy consumption are two pressing global challenges, especially in arid regions, that require sustainable solutions in line with circular economic principles. This study investigates the feasibility of greywater recycling systems for a 10-floor residential building housing 425 occupants by optimizing non-potable water demand and energy consumption. The grey-box modeling approach and energy balance optimization analysis are used to identify effective practices for implementing greywater recycling through the evaluation of environmental and economic effects on the performance of residential buildings. The findings are that there are 18% and 40% savings in water and energy, respectively, with greywater recycling systems. The research concludes that maximum treatment and recovery efficiencies significantly enhance the performance of the systems. Thus, there are 2.25 million kWh of annual energy savings that can repay itself in 4.42 years, as well as savings in the long-term consequences. These findings contribute further to achieving the UN-SDGs on Clean Water and Sanitation (SDG 6) and Affordable and Clean Energy (SDG 7). This study contributes to a better understanding of optimizing greywater recycling systems that are practical and scalable for residential use and promote sustainable urban development with minimal environmental impacts.

International thermal comfort requirements, such as ASHRAE standards, are used for classroom design in many countries, such as Australia, despite these standards serving thermal preferences for adult office workers in the USA or Europe. Subjected to mismatched thermal guidelines, students can be thermally uncomfortable in classrooms that are not correctly designed for their needs, and education buildings may consume significant energy on heating and cooling that is not appropriate to the location. The objective of this study is to critically examine the appropriateness of ASHRAE thermal comfort standards for classrooms in climates equivalent to New South Wales, Australia. Through a systematised literature review, this paper presents findings in four key areas: the relationship between thermal comfort and (i) local climate areas, (ii) classroom building types, (iii) students’ thermal comfort preferences and (iv) air conditioning. The research finds that international thermal comfort standards do not always provide suitable guidance for classrooms in diverse climate zones. The research identifies that reliance on mechanical heating and cooling can fail to meet students’ thermal comfort needs and undermines global environmental sustainability goals. This paper recommends localised thermal comfort benchmarks tailored to NSW’s climatic and educational contexts, contributing to improved classroom design, student wellbeing and energy-efficient learning environments.