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Several factors are motivating the development of preventive, personalized, connected, virtual, and ubiquitous healthcare services. These factors include declining public health, increase in chronic diseases, an ageing population, rising healthcare costs, the need to bring intelligence near the user for privacy, security, performance, and costs reasons, as well as COVID-19. Motivated by these drivers, this paper proposes, implements, and evaluates a reference architecture called Imtidad that provides Distributed Artificial Intelligence (AI) as a Service (DAIaaS) over cloud, fog, and edge using a service catalog case study containing 22 AI skin disease diagnosis services. These services belong to four service classes that are distinguished based on software platforms (containerized gRPC, gRPC, Android, and Android Nearby) and are executed on a range of hardware platforms (Google Cloud, HP Pavilion Laptop, NVIDIA Jetson nano, Raspberry Pi Model B, Samsung Galaxy S9, and Samsung Galaxy Note 4) and four network types (Fiber, Cellular, Wi-Fi, and Bluetooth). The AI models for the diagnosis include two standard Deep Neural Networks and two Tiny AI deep models to enable their execution at the edge, trained and tested using 10,015 real-life dermatoscopic images. The services are evaluated using several benchmarks including model service value, response time, energy consumption, and network transfer time. A DL service on a local smartphone provides the best service in terms of both energy and speed, followed by a Raspberry Pi edge device and a laptop in fog. The services are designed to enable different use cases, such as patient diagnosis at home or sending diagnosis requests to travelling medical professionals through a fog device or cloud. This is the pioneering work that provides a reference architecture and such a detailed implementation and treatment of DAIaaS services, and is also expected to have an extensive impact on developing smart distributed service infrastructures for healthcare and other sectors.

Advances in 5G and the Internet of Things (IoT) have to cater to the diverse and varying needs of different stakeholders, devices, sensors, applications, networks, and access technologies that come together for a dedicated IoT network for a synergistic purpose. Therefore, there is a need for a solution that can assimilate the various requirements and policies to dynamically and intelligently orchestrate them in the dedicated IoT network. Thus we identify and describe a representative industry-relevant use case for such a smart and adaptive environment through interviews with experts from a leading telecommunication vendor. We further propose and evaluate candidate architectures to achieve dynamic and intelligent orchestration in such a smart environment using a systematic approach for architecture design and by engaging six senior domain and IoT experts. The candidate architecture with an adaptive and intelligent element (“Smart AAA agent”) was found superior for modifiability, scalability, and performance in the assessments. This architecture also explores the enhanced role of authentication, authorization, and accounting (AAA) and makes the base for complete orchestration. The results indicate that the proposed architecture can meet the requirements for a dedicated IoT network, which may be used in further research or as a reference for industry solutions.

The recent pandemic era of COVID-19 has shown social adjustment on a global scale in an attempt to reduce contamination. In response, academic studies relating to smart technologies have increased to assist with governmental restrictions such as social distancing. Despite the restrictions, architectural, engineering and construction industries have shown an increase in budget and activity. An investigation of the adjustments made in response to the pandemic through utilizing new technologies, such as the internet of things (IoT) and smart technologies, is necessary to understand the research trends of the new normal. This study should address various sectors, including business, healthcare, architecture, education, tourism and transportation. In this study, a literature review was performed on two web-based, peer-reviewed journal databases, SCOPUS and Web of Science, to identify a trend in research for the pandemic era in various sectors. The results from 123 papers revealed a focused word group of IoT, smart technologies, architecture, building, space and COVID-19. Overlapping knowledges of IoT systems, within the design of a building which was designed for a specific purpose, were discovered. The findings justify the need for a new sub-category within the field of architecture called “smart architecture”. This aims to categorize the knowledge which is required to embed IoT systems in three key architectural topics—planning, design, and construction—for building design with specific purposes, tailored to various sectors.

The complexity of the contemporary era challenges traditional methods and processes in architecture, exacerbated by diverse specializations, global production, and recent cultural, social, and technological shifts. Consequently, contemporary architecture responds to societal demands through innovative methods and tools. To maintain coherence in design objectives, explicit information on addressing contemporary concerns is essential. Systematizing informational flows becomes the language of Smart Architecture, utilizing informative patterns and design variations to address these challenges effectively. Starting with an analysis of the inherent characteristics of the modular system, considered both as a regulator of complexity and in its evolution within the architectural panorama influenced by significant socio-cultural and ideological transformations, this contribution introduces the concept of the meta-module. In the era of smart architecture, the module tends to evolve into a meta-module, serving as a generative tool for Smart Architecture. The meta-module integrates interconnected information to organize contemporary complexity, employing innovative design components across multiple scales to address various concerns. The originality of this contribution lies in a process of abstraction that transforms the concept of the module into that of a ‘meta-module’, as a multi-level support matrix for design, compatible with cutting-edge computer tools, ensuring coherence between design considerations and corresponding construction choices.

Smart city initiatives aim to enhance urban domains such as healthcare, transportation, energy, education, environment, and logistics by leveraging advanced information and communication technologies, particularly the Internet of Things (IoT). While IoT integration offers significant benefits, it also introduces unique challenges. This paper provides a comprehensive review of IoT-based management in smart cities. It includes a discussion of a generalized architecture for IoT in smart cities, evaluates various metrics to assess the success of smart city projects, explores standards pertinent to these initiatives, and delves into the challenges encountered in implementing smart cities. Furthermore, the paper examines real-world applications of IoT in urban management, highlighting their advantages, practical impacts, and associated challenges. The research methodology involves addressing six key questions to explore IoT architecture, impacts on efficiency and sustainability, insights from global examples, critical standards, success metrics, and major deployment challenges. These findings offer valuable guidance for practitioners and policymakers in developing effective and sustainable smart city initiatives. The study significantly contributes to academia by enhancing knowledge, offering practical insights, and highlighting the importance of interdisciplinary research for urban innovation and sustainability, guiding future initiatives towards more effective smart city solutions.

The continuously increasing complexity of modern and sustainable power and energy systems leads to a wide range of solutions developed by industry and academia. To manage such complex system-of-systems, proper engineering and validation approaches, methods, concepts, and corresponding tools are necessary. The Smart Grid Architecture Model (SGAM), an approach that has been developed during the last couple of years, provides a very good and structured basis for the design, development, and validation of new solutions and technologies. This review therefore provides a comprehensive overview of the state-of-the-art and related work for the theory, distribution, and use of the aforementioned architectural concept. The article itself provides an overview of the overall method and introduces the theoretical fundamentals behind this approach. Its usage is demonstrated in several European and national research and development projects. Finally, an outlook about future trends, potential adaptations, and extensions is provided as well.

Data analytics are now playing a more important role in the modern industrial systems. Driven by the development of information and communication technology, an information layer is now added to the conventional electricity transmission and distribution network for data collection, storage and analysis with the help of wide installation of smart meters and sensors. This paper introduces the big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as huge amount of data collection are firstly discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of the typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this paper. By dealing with huge amount of data from electricity network, meteorological information system, geographical information system etc., many benefits can be brought to the existing power system and improve the customer service as well as the social welfare in the era of big data. However, to advance the applications of the big data analytics in real smart grids, many issues such as techniques, awareness, synergies, etc., have to be overcome.

With the acceleration of global urbanization and the improvement of people’s expectations for quality of life, intelligent buildings have become an essential part of future urban development, especially in terms of landscape layout and design. How to achieve aesthetics, practicality, and sustainability Unity has become a critical issue that needs to be solved urgently. Based on the landscape layout of intelligent buildings, this study proposes an evaluation framework based on a deep learning algorithm, aiming at improving the quality and efficiency of landscape design through intelligent means. Traditional landscape design often depends on the empirical judgment of designers, needs more objective quantitative evaluation standards, and is challenging to adapt to large-scale and diversified application scenarios. Therefore, this study applies deep convolutional neural networks to the characteristic analysis and optimization of intelligent building landscape layout. By studying a large number of excellent landscape design cases, the model can independently extract the key elements that constitute an excellent landscape layout and generate high-quality personalized design solutions accordingly. Through experimental verification, the optimized model has significantly improved design novelty, environmental adaptability, and user satisfaction, reaching an increase of 15%, 20%, and 12%, respectively. This study also constructs a comprehensive evaluation system, covering visual aesthetics, ecological benefits, interactive experience, and other dimensions to quantify the effect of landscape layout. With the help of the data processing capabilities of deep learning, various design schemes can be comprehensively and objectively evaluated, providing strong support for the selection and decision-making of innovative building projects. Article Highlights Effectively pinpoint critical landscape layout traits of smart buildings, like green space distribution and etc. Show how landscape elements (such as lighting and vegetation) directly affect smart buildings’ operational efficiency. Combine theory and practice, offering tangible guidance to balance landscape beauty with smart building performance.

The application of artificial intelligence (AI) in tall buildings’ development provides transformative opportunities for facing population growth pressures and sustainability challenges in cities. This study presents a comprehensive review of both the current literature and the theoretical framework of AI and its role in construction, specifically analyzing the convergence of AI and skyscraper development. The research methodology combines scholarly sources, AI image generation techniques, an analytical approach, and a comparative analysis of traditional versus AI-enhanced approaches. This study identifies key domains where AI significantly impacts skyscraper evolution, including design optimization, energy management, construction processes, and operational efficiencies. It highlights short-term benefits like enhanced architectural design through rapid generative design iterations and material optimization, alongside long-term implications involving adaptive building technologies and sustainability enhancements. Additionally, it addresses the advantages and challenges of adopting AI in architecture, considering various factors (e.g., sustainability, security, and occupant well-being), as well as the impact of different climates on AI in architecture and construction. It also explores transformative applications across diverse skyscraper functions and how AI can bridge different cultures and technologies. The findings reveal AI’s substantial potential in TBs’ design and management, (i.e., structural optimization, energy saving, safety protocols, and operational efficiency) by leveraging innovative technologies such as machine learning, computer vision, and predictive modeling. In conclusion, AI’s dual role as both a revolutionary tool that enhances traditional architectural methods and a catalyst for new design paradigms prioritizing sustainability and resilience has been reflected. Ultimately, this research underscores the importance of balancing AI innovation with established architectural principles to foster a favorable urban future that embraces both technological advancement and foundational design values. This study serves as a base for future research in the AI field.

The article concerns the issue of intelligence-based design, which, during the design process undertaken by architects, signifies (according to the authors of the article) thinking about perceptual involvement in the built environment, designing together with people and for people and not forgetting about conveniences brought by technological progress. The way to smart cities, in respect of architectural solutions, leads (to a significant extent) through the smart design of multifunctional buildings based on the idea of sustainable development. The article-related research involved multiple case studies including three buildings, i.e., Asian Cross Road Over the Sea (ACROS) in Fukuoka, Kultur- und Kongresszentrum Luzern (KKL) in Luzern and Changsha Meixihu International Contemporary Art Museum (MICA) in Changsha. The above-named buildings, located in different countries, i.e., Japan, Switzerland and China, respectively, and erected within various time spans, i.e., the 1990s–2020, are characterized by primary common features—multifunctionality, large cubature and comparable program elements. The research presented in this article aimed to find and present the elements of intelligence-based design in the buildings and perform their comparative analysis taking into consideration the fact that the buildings were erected within the span of 30 years. The article presents a graphic comparative analysis of the intelligence-based design, a multicriterial case study (encompassing the concept, functional and spatial solutions and structure) of selected architectural objects. The article includes also a graphic comparative analysis of the very objects and concert halls: Fukuoka Symphony Hall (ACROS), Salle Blanche (KKL) and Hunan Grand Theatre (MICA).