The lack of proper integration of inclusive design, accessibility standards, and universal design principles into urban planning has resulted in public open spaces that exclude many individuals, particularly those with disabilities or other marginalized groups. Integrating these principles is essential to create environments that are accessible, equitable, and beneficial for all individuals, regardless of their abilities, backgrounds, or socioeconomic status. To address this gap, this study analyzes existing research on universal design and accessibility standards to identify challenges and opportunities in the design of inclusive public open spaces. This systematic review seeks to critically explore how the application of universal design principles and accessibility standards supports the creation of inclusive public open spaces. Although universal design focuses on physical accessibility, inclusion in public spaces entails a more complex web of spatial, social, and policy factors. This research systematically evaluates international literature to determine key gaps, best practices, and action-oriented policy and design recommendations. The scope is situated within the Global South, particularly India, to align with the paper’s geographical focus. The findings emphasize that robust enforcement structures, contextual adjustments, and global standards are crucial for the successful implementation of universal design and accessibility integrated with inclusive design. This integration must begin at the initial stages of the design process and be maintained throughout planning, construction, management, and operation. The study further highlights the importance of stakeholder involvement as a critical component at every stage of the design and implementation process. It underscores the need for tailored strategies for urban spaces that incorporate cultural, regional, and socioeconomic characteristics. Additionally, the study highlights the potential of technology and innovation, such as digital accessibility tools and smart city efforts, to improve inclusivity. Finally, the study proposes future research directions, including the impact of inclusive design on social cohesion, the challenges faced in rural and peripheral areas, and the role of modern technology in enhancing public open space design.

In developing economies, residential energy consumption patterns have rapidly transformed with better energy access and service quality. Unlike other building types, residential buildings are more complex due to wide variations in their consumption patterns influenced by various factors. Researchers have characterised residential building stock based on distinct building archetypes. This paper presents a comprehensive review of relevant published research focusing on the classification of residential buildings based on their energy consumption. This review also focuses on residential archetype studies in the context of building science. The methodologies adopted by different researchers to characterise the energy use of residential building stock using an archetypal approach at different spatial scales (building to city scale and local to national scale) have been critically reviewed in this study. The paper will provide the researchers with a holistic understanding of the current directions and magnitude of ongoing research in this domain.

India’s fossil-fuel-based energy dependency is up to 68%, with the commercial and residential sectors contributing to the rise of building energy demand, energy use, and greenhouse gas emissions. Several studies have shown that the increasing building energy demand is associated with increased space-cooling ownership and building footprint. The energy demand is predicted to grow further with the conditions of global warming and the phenomenon of urban heat islands. Building designers have been using state-of-the-art transient simulation tools to evaluate energy-efficient envelopes with present-day weather files that are generated with historical weather datasets for any specific location. Designing buildings with historical climatic conditions makes the buildings vulnerable to the predicted climate change impacts. In this paper, a weather file generator was developed to generate Indian future weather files using a geo-filtering-based spatial technique, as well as the temporal downscaling and machine learning (ML)-based bias correction approach proposed by Belcher et al. The future weather files of the three representative concentration pathways of 2.6, 4.5, and 8.5 could be generated for the years 2030, 2050, 2070, 2090, and 2100. Currently, the outputs of the second-generation Canadian Earth System Model are being used to create future weather files that will aid architects, urban designers, and planners in developing a built environment that is resilient to climate change. The novelty lies in using observed historical data from present-day weather files on the typical meteorological year for testing and training ML models. The typical meteorological weather files are composed of the concatenation of the monthly weather datasets from different years, which are referred to for testing and training ML models for bias correction.

Historic religious cities are living examples of cultural landscapes where spiritual traditions, heritage, and visitor experiences combine to demonstrate a timeless experience. It is very challenging to achieve balance among the demands of mass pilgrimage, heritage preservation, and urbanization. Govardhan, India is a Hindu religious town with historical significance. Millions of pilgrims travel to Govardhan every year to perform parikrama and take a holy dip in kunds. The quality of the visitor experience, spatial coherence, and heritage conservation are all at risk due to increasing urbanization and tourism. The study intends to create a paradigm for the sustainable management of religious heritage towns by evaluating the factors involving visitor perception, historical significance, and spatial visibility, employing a combination of computational methods and cognitive assessments. The study employed space syntax tools (visibility graph analysis and isovist area analysis) to quantify spatial significance (SS) and identify patterns of openness, congestion, and visibility along the parikrama route of Govardhan. By examining pilgrims’ cognitive surveys for openness, orientation, congestion, and spiritual impression, a cognitive index (CI) and heritage importance scores (HIS) have been developed. The computed spatial significance (SS) has been correlated with cognitive index (CI) and heritage importance (HIS) scores to create an experiential priority index (EPI). The study employs a mixed-method approach that incorporates heritage significance scoring, cognitive surveys, and spatial analytics, including methods such as the isovist area analysis and visibility graph analysis. In order to assess how spatial arrangement and intangible perceptions together influence visitor experience, these statistics are further combined using a composite experiential priority index (EPI). The findings show a strong correlation between spiritual orientation, visual connectivity, and spatial openness; locations such as ‘punchari ka lota temple’ and ‘kusum sarovar’ are high-priority nodes. In accordance with United Nation Sustainable Development Goals (SDGs) (11, 9, 12, 4.7, and 8.9), this research proposes a heritage impact assessment (HIA) framework that provides workable solutions for ecological restoration, heritage-sensitive zoning, sustainable pilgrimage management, and enhanced tourism.