AI-Based Physical and Virtual Platform with 5-Layered Architecture for Sustainable Smart Energy City Development

Developing Human-Centered Urban Digital Twins for Community Infrastructure Resilience: A Research Agenda

Urban digital twins (UDTs) have been identified as a potential technology to achieve digital transformative positive urban change through landscape architecture and urban planning. However, how this new technology will influence community resilience and adaptation planning is currently unclear. This article: (1) offers a scoping review of existing studies constructing UDTs, (2) identifies challenges and opportunities of UDT technologies for community adaptation planning, and (3) develops a conceptual framework of UDTs for community infrastructure resilience. This article highlights the need for integrating multi-agent interactions, artificial intelligence, and coupled natural-physical-social systems into a human-centered UDTs framework to improve community infrastructure resilience.

The Dual Role of Artificial Intelligence in Developing Smart Cities

Defining smart city pillars, and their nature and essence, continues to be debated in the scientific literature. The vast amount of information collected by electronic devices, often regarded merely as a means of rationalizing the use of resources and improving efficiency, could also be considered as a pillar. Information by itself cannot be deciphered or understood without analysis performed by algorithms based on Artificial Intelligence. Such analysis extracts new forms of knowledge in the shape of correlations and patterns used to support the decision-making processes associated with governance and, ultimately, to define new policies. Alongside information, energy plays a crucial role in smart cities as many activities that lead to growth in the economy and employment depend on this pillar. As a result, it is crucial to highlight the link between energy and the algorithms able to plan and forecast the energy consumption of smart cities. The result of this paper consists in the highlighting of how AI and information together can be legitimately considered foundational pillars of smart cities only when their real impact, or value, has been assessed. Furthermore, Artificial Intelligence can be deployed to support smart grids, electric vehicles, and smart buildings by providing techniques and methods to enhance their innovative value and measured efficiency.

City Digital Twin Potentials: A Review and Research Agenda

The city digital twin is anticipated to accurately reflect and affect the city’s functions and processes to enhance its realization, operability, and management. Although research on the city digital twin is still in its infancy, the advancement of the digital twin technology is growing fast and providing viable contributions to augmenting smart city developments. This study reviews the literature to identify the current and prospective potentials and challenges of digital twin cities. A research agenda is also proposed to guide future research on the city digital twincity digital twin to reach the utmost level of a comprehensive and complete city digital twin. Enhancing the efficiency of data processing, promoting the inclusion of socio-economic components of the city, and developing mutual integration between the two counterparts of the digital twin are proposed to be the future research directions to achieve and utilize a completely mirrored city digital twin.

Digital Twin Technologies for Turbomachinery in a Life Cycle Perspective: A Review

Turbomachinery from a life cycle perspective involves sustainability-oriented development activities such as design, production, and operation. Digital Twin is a technology with great potential for improving turbomachinery, which has a high volume of investment and a long lifespan. This study presents a general framework with different digital twin enabling technologies for the turbomachinery life cycle, including the design phase, experimental phase, manufacturing and assembly phase, operation and maintenance phase, and recycle phase. The existing digital twin and turbomachinery are briefly reviewed. New digital twin technologies are discussed, including modelling, simulation, sensors, Industrial Internet of Things, big data, and AI technologies. Finally, the major challenges and opportunities of DT for turbomachinery are discussed.

Employing Emerging Technologies to Develop and Evaluate In-Vehicle Intelligent Systems for Driver Support: Infotainment AR HUD Case Study

The plurality of current infotainment devices within the in-vehicle space produces an unprecedented volume of incoming data that overwhelm the typical driver, leading to higher collision probability. This work presents an investigation to an alternative option which aims to manage the incoming information while offering an uncluttered and timely manner of presenting and interacting with the incoming data safely. The latter is achieved through the use of an augmented reality (AR) head-up display (HUD) system, which projects the information within the driver’s field of view. An uncluttered gesture recognition interface provides the interaction with the AR visuals. For the assessment of the system’s effectiveness, we developed a full-scale virtual reality driving simulator which immerses the drivers in challenging, collision-prone, scenarios. The scenarios unfold within a digital twin model of the surrounding motorways of the city of Glasgow. The proposed system was evaluated in contrast to a typical head-down display (HDD) interface system by 30 users, showing promising results that are discussed in detail.

An Intelligent Waste Removal System for Smarter Communities

With the continuous progress of urbanization, the discharge of municipal solid waste has profoundly affected human production/living and social ecological health, and waste disposal has become one of the key issues all over the world. In the context of intelligent technology, this paper innovates the way of waste disposal according to the development direction of a smart city and the requirement of sustainable development strategy. An intelligent urban waste removal system is developed using a ROS (Route Operation System) robot operating system and RRT (Rapid Exploration of Random Trees) path planning algorithm. With a background of data management, the entire process of intelligent automatic waste removal is triggered by automatic communication from individual waste bins to a waste collection vehicle (WCV) where the bin needs to be emptied, and the automatic collection and transportation by the WCV in response. In combination with the IoT (Internet of Things), the system provides scientific data support for the intelligent layout of communities and even urban waste bins to greatly enhance the development of intelligence communities and smart cities.

Smart Building Integration into a Smart City (SBISC): Development of a New Evaluation Framework

The aim of this study is to define the features that smart buildings should fulfil in order to be compatible with the overall context of the smart city and to introduce a new evaluation framework of Smart Buildings Integration into a Smart City (SBISC). By analysing scientific literature as well as existing international and local project examples, the features of smart buildings that are expected to be adopted in smart cities were identified. The SBISC evaluation methodology was developed and applied to a set of selected projects. The literature review revealed that the smart building and smart city concepts were developed in different time frames and by different stakeholders and, thus, need to be realigned. The most important aspect is to employ in a smart building all the functionalities proposed by the smart areas of the city and vice versa by enabling the recommended features of smart materials, smart building services, and smart construction to serve for the surrounding systems. Nine office buildings representing smart building concept in different smart cities built within the period 2007–2018 with a total area from 10,000 m2 to 143,000 m2 were selected for the analysis. The research of selected projects revealed that the smart buildings have more potential to become smarter by utilizing smart cities capabilities in the areas of smart energy, smart mobility, smart life, and smart environment. Smart cities are the most prominent trend in creating a cohesive environment.

From Intelligent Energy Management to Value Economy through a Digital Energy Currency: Bahrain City Case Study

The transition of the energy system into a more efficient state requires innovative ideas to finance new schemes and engage people into adjusting their behavioural patterns concerning consumption. Effective energy management combined with Information and Communication Technologies (ICTs) open new opportunities for local and regional authorities, but also for energy suppliers, utilities and other obligated parties, or even energy cooperatives, to implement mechanisms that allow people to become more efficient either by producing and trading energy or by reducing their energy consumption. In this paper, a novel framework is proposed connecting energy savings with a digital energy currency. This framework builds reward schemes where the energy end-users could benefit financially from saving energy, by receiving coins according to their real consumption compared to the predicted consumption if no actions were to take place. A pilot appraisal of such a scheme is presented for the case of Bahrain, so as to simulate the behaviour of the proposed framework in order for it to become a viable choice for intelligent energy management in future action plans.

Moving towards a Smarter Housing Market: The Example of Poland

Cities are currently undergoing vast changes, which have very significant implications for the functioning of the housing market. In particular, it should be stated that the traditional residential market, in imitation of the smart city concept, is becoming increasingly smarter. This smartness can be expressed in four dimensions: the “automatic” rental housing market; innovative digital platforms in the traditional housing market; innovative policies and housing models; and the ability to forecast demand on the housing market, which together form the so-called smart housing concept. On this basis, this study attempted to assess empirically the smartness of the residential markets in Polish provincial capitals. Firstly, after a thorough analysis of digital housing portals, official websites of Polish provincial capitals and public statistics data, the smart housing concept was operationalised in all its dimensions by defining appropriate indicators measuring its level in a given city. Then, using the zero unitarization and entropy weight methods, followed by a no-pattern synthetic measure, a comprehensive smart housing index was obtained for each city investigated. Research results showed that there is a large degree of variation in the level of smartness of the housing markets in the examined cities. Furthermore, the analysis also indicates that the economic dimension of the smart city concept and the co-working concept are the main driving forces behind the development of smart residential markets. In addition, the study reveals that the implementation of the smart housing concept has a positive impact on the quality of life of city inhabitants.

Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis

As urbanization continues to accelerate, the number of cities and their growing populations have created problems, such as the congestion and noise related to transportation, the pollution from industry, and the difficulty of disposing of garbage. An emerging urban strategy is to make use of digital technologies and big data to help improve the quality of life of urban residents. In the past decade, more and more researchers have studied smart cities, and the number of literature in this field grows rapidly, making it “big data”. With the aim of better understanding the contexts of smart-city research, including the distribution of topics, knowledge bases, and the research frontiers in the field, this paper is based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) in the Web of Science (WoS) Core Collection, and the method used is that of comprehensive scientometric analysis and knowledge mapping in terms of diversity, time slicing, and dynamics, using VOSviewer and CiteSpace to study the literature in the field. The main research topics can be divided into three areas—“the concepts and elements of the smart city”, “the smart city and the Internet of Things”, and “the smart city of the future”—through document co-citation analysis. There are four key directions—“research objectives and development-strategy research”, “technical-support research”, “data-processing and applied research”, and “management and applied research”—analyzed using keywords co-occurrence. Finally, the research frontiers are urban-development, sustainable cities, cloud computing, artificial intelligence, integration, undertaken through keyword co-occurrence analysis.