In the present state of manufacturing industries, industrial and commercial components have been prepared for low energy consumption and high performance. Recent and emerging nanoparticles and nanofluid technologies must be incorporated into advanced manufacturing processes to improve the performance of sustainable materials and manufacturing processes. It is essential to assess the activities involved in nanoparticle and nanofluid applications, identify the potential impacts, and discuss various utilization methods for nanoparticles and nanofluids, the economy, the environment, and engineering applications. Sustainable Utilization of Nanoparticles and Nanofluids in Engineering Applications provides the latest research and significant potential to apply nanomaterials and nanofluids in various engineering applications. It is a reference guide to provide real-life problems with feasible potential systems, models, and examples related to the application, synthesis, innovations, and properties of advanced nanomaterials and nanofluids. Covering key topics including sustainable development, utilization, and innovation of nanoparticles and nanofluids, this reference work is ideal for industry professionals, material scientists, manufacturing industry professionals, material selectors, design engineers, machine instructors, administrators, researchers, academicians, postgraduates, scholars, and instructors.

As society transitions into the digital age, the demand for advanced robotics and autonomous systems has remained unchanged. However, the field faces significant challenges bridging the gap between current capabilities and the potential for brilliant, autonomous machines. While exact and efficient, current robotic systems need more sophistication and adaptability of human intelligence. This limitation restricts their application in complex and dynamic environments, hindering their ability to realize their potential fully. Multidisciplinary Applications of AI Robotics and Autonomous Systems addresses these challenges by presenting cutting-edge research and innovative robotics and autonomous systems solutions. By exploring topics such as digital transformation, IoT, AI, and cloud-native computing paradigms, readers will understand the latest advancements in the field. The book delves into theoretical frameworks, computational models, and experimental approaches, offering insights to help researchers and practitioners develop more intelligent and autonomous machines.

The construction industry, a cornerstone of modern development, must meet the growing demand for new buildings while minimizing environmental impact. As global populations rise and living standards improve, the need for sustainable building practices has never been more apparent. Traditional construction methods and materials contribute significantly to carbon emissions, resource depletion, and biodiversity loss. Addressing these issues requires innovative solutions that balance development needs with environmental stewardship. Innovations in Energy Efficient Construction Through Sustainable Materials offers a comprehensive response to this pressing problem. The book explores pioneering approaches to building design and construction, focusing on the use of alternative, low-carbon materials and advanced technologies. It provides an in-depth analysis of current and future trends in sustainable construction, covering topics such as recycling waste materials, utilizing biodegradable resources, and implementing energy-efficient designs. By presenting a variety of research fields and practical applications, the book bridges the gap between theoretical concepts and real-world solutions, making it an essential resource for industry professionals, researchers, and advanced students.

In the age of immediate technical expansion, our world faces a multifaceted challenge: ensuring the sustainability of our digital transformation. Governments and organizations have wholeheartedly embraced innovative technologies such as artificial intelligence, blockchain, and e-governance, but in doing so, they have encountered a complex web of issues. These range from cybersecurity concerns in an increasingly digitalized world to the need for intelligent systems capable of managing automation infrastructure and interconnected environments. Sustainable Development in AI, Blockchain, and E-Governance Applications offers a forward-thinking approach that harnesses the synergy between intelligent systems, machine learning, deep learning, and blockchain methods. It explores data-driven decision-making, automation infrastructure, autonomous transportation, and the creation of connected buildings, all aimed at crafting a sustainable digital future. By delving into topics like machine learning for smart parking, disease classification through neural networks, and the Internet of Things (IoT) for smarter cities, this book equips academic scholars with the tools they need to navigate the complex terrain of technology and governance. Academic scholars and researchers in technology, governance, and sustainability will find this book to be an indispensable resource. It caters to those seeking a comprehensive understanding of current and future trends in the integration of intelligent systems with cybersecurity applications.

The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development.

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.

The application of genetic engineering techniques by redesigning and repurposing biological systems for novel biotechnical applications has paved the way for the field of synthetic biology. This field boosted the evolution and discovery of various novel technologies essential to the conquest of biological problems related to health, disease, the environment, and energy. The field of synthetic biology is growing rapidly, and further research is required. Applications of Synthetic Biology in Health, Energy, and Environment deliberates on principles and the advancement of synthetic biology and their translation in the fields of health, disease, energy, and the environment. Covering topics such as climate change, bioremediation, and smart drugs, this premier reference source is an excellent resource for students and educators of higher education, industrialists, medical professionals, hospital administrators, policymakers, environmental scientists, pharmacists, librarians, researchers, and academicians.