In the past decades, protecting the urban environment in the face of environmentalism and environmental rights has become crucial to saving the planet from the dangers of the rapid urban development of new cities and societies. Air temperature is one of the factors influenced by climate change and contemporary city morphology that lacks compact city features. Contemporary cities have taken on global paradigms, adopting open-fabric, multiple, and ultrahigh residential towers and superhuman-scale spaces at the level of squares and public parks. This type of planning results in a radical thermal transformation not only in the movement and transportation network, but also in all public spaces and their external spaces. It is essential to understand the dimensions and principles of urban planning and design in conjunction with the competence of environmental design to reduce the impact of the urban heat island (UHI) phenomenon. Remapping Urban Heat Island Atlases in Regenerative Cities focuses on public health and wellbeing, decent work and economic growth, sustainable cities and societies, and climate action. It presents atlases of UHI-based digital techniques and methods of modelling as well as the use of these atlases, mapping, and models in exploring the placemaking problems in the new cities. Covering topics such as artificial intelligence, pedestrian density mapping, and urban heat island mitigation, this premier reference source is a critical resource for architects, city planners, urban planners, city officials, government officials, policymakers, non-profit organizations, politicians, engineers, libraries, students and educators of higher education, researchers, and academicians.

Recently, a new digital twin consortium has been established that aims to deploy digital twin technology in new markets as well as in the development of smart cities. Designing smart cities, smart communities, and smart ecosystems powered by optimal digital twin deployments is a vision that currently only futurists can entertain and requires some time to reach large-scale adoption. However, it is incumbent upon us as a society to educate and train future generations on how to leverage digital twin technologies in order to optimize our daily lives as well as increase our efficiency, productivity, and safety. Impact of Digital Twins in Smart Cities Development provides insights regarding the global landscape for current digital twin research and deployments and highlights some of the challenges and opportunities faced during large-scale adoptions. Critical domains such as ethics, data governance, cybersecurity, inclusion, diversity, and sustainability are also addressed and considered. Covering topics such as digital identity and digital economics, this reference work is ideal for urban planners, engineers, policymakers, industry leaders, scientists, economists, academicians, practitioners, researchers, instructors, and students.

In recent years, the world of civil engineering has been changing considerably. Within the many obstacles, barriers, and opportunities, significant challenges should be considered for the future of civil engineering. With the contribution of geoinformatics, several scientific areas associated with civil engineering experienced rapid technological evolution. Considering these challenges, the future of civil engineering can be portrayed. Geoinformatics in Support of Urban Politics and the Development of Civil Engineering portrays the evolution of the world of civil engineering, what happened in recent decades, what will develop in the future, and what the path will be. This work characterizes the different academic areas of civil engineering, demonstrating its evolution. Covering topics such as landslide susceptibility mapping, spatial data, and local development, this premier reference source is an essential resource for policymakers, environmentalists, scientists, technicians, decision makers, engineers, students and educators of higher education, librarians, researchers, and academicians.

In recent years, artificial intelligence (AI) has drawn significant attention with respect to its applications in several scientific fields, varying from big data handling to medical diagnosis. A tremendous transformation has taken place with the emerging application of AI. AI can provide a wide range of solutions to address many challenges in civil engineering. Artificial Intelligence and Machine Learning Techniques for Civil Engineering highlights the latest technologies and applications of AI in structural engineering, transportation engineering, geotechnical engineering, and more. It features a collection of innovative research on the methods and implementation of AI and machine learning in multiple facets of civil engineering. Covering topics such as damage inspection, safety risk management, and information modeling, this premier reference source is an essential resource for engineers, government officials, business leaders and executives, construction managers, students and faculty of higher education, librarians, researchers, and academicians.

There is an urgent need to emphasize inclusivity in architecture and the built environment. Innovative technologies within the field of architecture are being developed to enhance inclusivity in architectural approaches and development processes. It is essential to research inclusivity in architecture and the built environment toward holistic sustainable development. The Handbook of Research on Inclusive and Innovative Architecture and the Built Environment discusses inclusive and innovative approaches to providing socio-cultural value within architecture and the built environment. It focuses on issues of diversity, sustainability, resilient designs, and more. Further, the book expands the knowledge and awareness of architecture and the built environment towards inclusivity in design development and emerging advanced technology. Covering topics such as architectural challenges, global health, and urban morphology, this major reference work is an excellent resource for architects, government officials, urban planners, practitioners, students and educators of higher education, researchers, and academicians.

Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.