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.

Today, the global power demand relies on a delicate balance between conventional and renewable energy systems, necessitating both efficient power generation and the effective utilization of these energy resources through appropriate energy storage solutions. Integrating microgrid systems into the utility grid has become a critical facet of modern power systems. The intermittent and unpredictable nature of these energy sources poses a formidable challenge for academic scholars and researchers. This compels them to explore under-investigated areas, including energy source estimation, storage elements, load pattern prediction, coordination among distributed sources, and the development of energy management algorithms for precise and efficient control. AI Approaches to Smart and Sustainable Power Systems tackles these issues using cutting-edge AI techniques. It examines the most effective methods to optimize voltage, frequency, power, fault diagnosis, component health, and overall power system quality and reliability. AI empowers predictive and preventive maintenance for a sustainable energy future. The book focuses on emerging research areas, including renewable energy, power flow calculations, demand scheduling, real-time performance validation, and AI integration into modern power systems, accompanied by insightful case studies.

Engineering plays a major role in solving real-world problems, from small inconveniences to societal or global concerns around food scarcity, water shortages, environmental damage, problems in housing or infrastructure and more. In today's rapidly evolving world, the development of the latest generation of engineering and technology is crucial for maintaining productivity, innovation, and improving our overall quality of life. Intelligent Engineering Applications and Applied Sciences for Sustainability is an essential research book that serves as a compilation of cutting-edge research and advancements in engineering, science, and technology, and more importantly, how the application of these advancements will guide the path to a more sustainable future. This book focuses on intelligent engineering applications, which encompass the design and implementation of embedded technologies in various domains. It covers a wide range of fields and their influence on the Sustainable Development Goals (SDGs), fostering interdisciplinary approaches and innovative solutions, including additive manufacturing technologies, aerospace science and engineering, agricultural advancements, computer science for sustainable development, applied biosciences, applied mathematics, industrial engineering, robotics and automation, transportation, future mobility, and much more. As an academic, rigorous exploration of various disciplines, this book serves as an invaluable resource for researchers, scholars, and professionals seeking to advance the frontiers of intelligent engineering applications and applied sciences for a sustainable future.

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.

Infrastructure development presents significant challenges for both developing and developed countries, hindering their progress in achieving the Sustainable Development Goals (SDGs). Governments often struggle to effectively leverage the necessary resources and expertise for financing and managing infrastructure projects, resulting in untapped potential for sustainable and inclusive development. Achieving the Sustainable Development Goals Through Infrastructure Development, edited by Cristina Raluca Gh. Popescu, Poshan Yu, and Yue Wei, offers a comprehensive guide to address these challenges. Focusing on public-private partnerships (PPPs) as a transformative solution, the book equips policymakers, investors, practitioners, and researchers with the essential knowledge and tools needed to navigate the complexities of infrastructure development and leverage the expertise and resources of the private sector. By showcasing successful case studies, analyzing critical success factors, and providing valuable insights into the implementation of PPPs in both developing and developed countries, this book becomes an indispensable resource for driving progress towards the SDGs. Covering crucial topics such as financing, risk management, legal frameworks, and sustainability considerations, it empowers readers to make informed decisions and foster collaborative partnerships between the public and private sectors. Through its comprehensive roadmap, this book enables stakeholders to unlock the full potential of sustainable and inclusive infrastructure development, paving the way for a prosperous future for all.

Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship. This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages.

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.

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.

Renewable Energy for Plug-In Electric Vehicles: Challenges, Approaches, and Solutions for Grid Integration provides a holistic guide to the critical technical challenges of integrating renewable energy for grid-connected electric vehicles. Considering the impact of renewable energy integration from a wide range of perspectives, this book leverages its global range and expertise to cover problems from power stability to market strategies, fast charging, and cybersecurity. Practical solutions are provided, incorporating the latest advances in technologies across meters, sensors, batteries, storage, demand response, artificial intelligence, and power system design.Supporting broad understanding and practical solution development, the book enables researchers, students, and industry professionals to take the next steps towards renewably sourced, grid-integrated electric vehicles. - Focuses on the essential step of integrating grid-charging electric vehicles with renewable energy sources - Provides comprehensive analysis of the challenge renewable integration presents for existing electric vehicle technologies - Breaks down real-world, practical case studies and solutions using the latest advances by a global team of experts