The continuous growth of urban populations and the complexities of their current management in Africa have driven local governments to explore new technologies to optimize their urban and territorial performance. These governments and related stakeholders’ resort to the term “smart city” to orient the current urban planning policies and practices to be more efficient and adequate. Nevertheless, the issue that remains is how to contextualize this global term that has not yet been fully adopted by African cities that have claimed to be “Smart”. This contextualization becomes more complex in this critical context, where the city has not yet reached an ideal performance. Therefore, to reach this prospective African smart city, a critical review of how it would be both human-centered and techno-centered is imperative. This paper would review accordingly the above argument and set key performance indicator-based methodology on how to evaluate the smartness of a city in the African context.

In recent decades, the Saïss plain, in the northwest of Morocco, has experienced a noticeable increase in water demand due to a very significant population growth and economic development, as well as the climate change effects. With the aim of reaching optimal and dynamic management of these water resources, it is essential to have comprehensive and reliable information on the state of the aquifer systems in the region. To achieve this, we assessed a geostatistical analysis of groundwater level data, and created a multivariate regression model. Indeed, in this study, a spatiotemporal analysis of groundwater depth based on piezometric measurements of 45 wells was carried out for the period from 2005 to 2020. It compares and evaluates eight geostatistical interpolation methods and solves the problem of data gaps of the piezometric measurement by completing the chronological series of the groundwater level between 2005 and 2020 using the ARIMA model. The results demonstrate that the variation in the groundwater level between 2005 and 2020 indicates that the water table level is decreased in certain areas, but it has improved or remained constant in other areas. These results emphasize an urgent need for a dynamic management for the conservation of groundwater resources in certain areas of the region under this study.

In this paper, an optimization-based analysis approach is presented to cost-effectively improve the energy efficiency of residential buildings in Morocco. This study introduces a unique focus on the Moroccan context, where a comprehensive application of energy efficiency optimization has not yet been undertaken. This analysis considers the interactive effects among various energy efficiency measures to determine optimal combinations for designing high-energy performance, as well as net-zero energy, residential buildings for six climate zones in Morocco. In particular, the design analysis approach combines a whole-building simulation with the sequential search technique, providing a novel, integrated cost–benefit analysis that minimizes lifecycle costs (LCC) while maximizing energy savings for each climate zone. This study also includes an unprecedented comparison of optimized designs, reference designs, and current Moroccan building regulations (RTCM), highlighting potential improvements to the existing regulatory framework. While the sequential search method has been applied elsewhere, its specific application to achieve net-zero energy homes in the Moroccan context with comparable LCC is a new contribution. The analysis results show that houses in Morocco can be cost-effectively designed to achieve annual energy savings of 51% for Zone 1, 53% for Zone 2, 60% for Zone 3, 67% for Zone 4, 54% for Zone 5, and 56% for Zone 6 compared to the current construction practices considered as reference designs. Moreover, the results indicate that houses can reach net-zero energy building designs with almost the same LCC as the reference design cases for all the climate zones in Morocco.

With the rapid urbanization occurring across African cities, the emergence of a middle class is exerting its influence on the urban form and structure. Matching their social status and drawing on global influences, the housing characteristics of this class are distinctive in spatial organization, material choice, and location, among others. Understanding these emerging typologies is critical for urban housing policy to be responsive to the needs and preferences of this class. The present paper aims first to develop a new approach for defining the middle class in the African context and second, to analyze its housing typology through a multidimensional analysis based on housing attributes and socio-economic characteristics in Casablanca City. A data-driven approach based on principal component analysis (PCA) has been used to define multidimensionally the middle class and its housing typology. Through the construction of a multidimensional composite index to measure middle class, the study highlighted that middle-class housing is characterized by an adequate condition, a suitable size (two to three rooms), and affordability between 8000 and 11,000 Moroccan dirhams (MAD) per square meter. In addition, although the Moroccan modern houses (two-floor single-family housing) and apartments (four floors or greater) are the most occupied by the middle class, the study showed that as income and social mobility increase, the apartment building and the villa are increasingly preferred to the Moroccan modern house.

Urban Digital Twins (UDTs) are emerging as a new paradigm in smart city strategies, enabling real-time interaction with urban environments and supporting data-driven decision-making. By expanding beyond traditional smart functions, UDTs facilitate the analysis and simulation of urban resilience and sustainability indicators within a virtual city ecosystem, addressing both immediate urban challenges and long-term planning goals. This paper introduces TwinCity, a city-scale Urban Digital Twin framework developed and validated through a case study of the Green City of Benguerir, Morocco. The framework incorporates a technical architecture based on semantic 3D city models, data integration, and simulation scenarios to analyse the solar energy potential of the rooftop, the energy consumption of the building and the morphological indicators. A user-friendly web interface was developed to visualise and interact with the UDT, ensuring its accessibility. By bridging the gap between technical challenges (such as data scarcity) and practical applications, this work offers a replicable model for cities in the Global South.

This paper systematically reviews scientific papers to understand the primary forms of HI, why they arise, and how they affect the urban landscape. It addresses the question, “What are the key trends, drivers, and impacts of Housing Informality (HI), and what methods researchers use to study the latter?”. Previous research addressed the trends, drivers, impacts, and methods individually, failing to adopt a holistic perspective that could clarify HI as a core scientific concept distinct from informal housing. Accordingly, this systematic literature review (SLR) explores 541 scientific peer-reviewed publications from Scopus, Web of Science, and Google Scholar. By utilizing a PRISMA framework, we reduced the number of documents to 27, which we thoroughly analyzed. The results highlight five main trends of HI around the globe: unauthorized modifications, informal market dynamics, Accessory Dwelling Units (ADUs), squatting, and unusual housing. These trends are induced by several economic and sociocultural drivers that address the gap between regulations and governance from one side and lived realities from another, resulting in economic, social, legal, health, and urban impacts.