Image Processing In Renewable Energy Resources Opportunities And Challenges

This book is a compilation of innovative work on image processing applications for renewable energy systems. The chapters in the book describe the use of neural networks in multi-direction dynamic, topographical data frameworks which are designed to account for the distinctive contemporary issues faced when managing environmentally friendly power generation systems. The topics covered include uncertainty analysis methods, computing technologies, automated control systems, performance analysis, riverfront analysis through image processing and solar power estimation methods, to name a few. The information is also complemented with a review of problems in the electric power sector in India. This book is beneficial for professionals and researchers who work on hybrid techniques of GIS, remote sensing, image processing and the implementation of these techniques for utilizing renewable energy resources. Engineers who work on advanced algorithms for renewable energy applications will also get an updated perspective about relevant innovations in this industrial sector.

Demand for energy and water is increasing as a result of rapid economic, population, and industrial growth. By 2050, it is expected that global energy consumption will nearly double in tandem with world water demand. Because of competing demands for finite resources, existing water and energy systems are limited in their ability to satisfy these expanding needs. Furthermore, rapid population and industrial development inevitably result in the generation of a significant amount of wastewater laden with toxins, persistent inorganic and organic pollutants, and other toxic emissions emitted from different sources. Opportunities and Challenges in Climate-Friendly Clean Water and Energy Technologies presents the most recent technological advancements that are relevant to environmentally friendly methods of producing clean water and a sustainable supply of energy. In order to protect against climate change, it also highlights the most recent empirical research findings in the field of cutting-edge industrial and transportation emission reduction measures. Covering key topics such as renewable energy, wastewater treatment, and biomaterials, this reference work is ideal for environmental scientists, industry professionals, researchers, practitioners, academicians, instructors, and students.

The United States and China are the world's top two energy consumers and, as of 2010, the two largest economies. Consequently, they have a decisive role to play in the world's clean energy future. Both countries are also motivated by related goals, namely diversified energy portfolios, job creation, energy security, and pollution reduction, making renewable energy development an important strategy with wide-ranging implications. Given the size of their energy markets, any substantial progress the two countries make in advancing use of renewable energy will provide global benefits, in terms of enhanced technological understanding, reduced costs through expanded deployment, and reduced greenhouse gas (GHG) emissions relative to conventional generation from fossil fuels. Within this context, the U.S. National Academies, in collaboration with the Chinese Academy of Sciences (CAS) and Chinese Academy of Engineering (CAE), reviewed renewable energy development and deployment in the two countries, to highlight prospects for collaboration across the research to deployment chain and to suggest strategies which would promote more rapid and economical attainment of renewable energy goals. Main findings and concerning renewable resource assessments, technology development, environmental impacts, market infrastructure, among others, are presented. Specific recommendations have been limited to those judged to be most likely to accelerate the pace of deployment, increase cost-competitiveness, or shape the future market for renewable energy. The recommendations presented here are also pragmatic and achievable.

Today, the relentless depletion of natural resources has reached a critical juncture, demanding innovative solutions. Advanced Geospatial Practices in Natural Environment Resource Management dives into the intricate tapestry of issues jeopardizing ecosystems. This book systematically dissects the fundamental drivers, traces the historical evolution, and elucidates the underlying causes that have led to this precarious point. From deforestation to pollution, from climate change to habitat destruction, these challenges are multifaceted. By harnessing the power of data-driven decision-making and predictive modeling, this book advocates for a profound shift in the approach to environmental issues. This book also explores the complexities of water, soil, and air-related challenges, offering technically sound solutions that strike a balance between legislative, economic, social, and political considerations. The holistic approach championed in these pages holds the potential to benefit governments, businesses, and communities alike. This book is ideal for a diverse audience, including students, scholars, and researchers, as well as environmental science enthusiasts, geospatial technology professionals, and AI/ML practitioners. Policymakers, environmental engineers, and professionals engaged in governmental and corporate sustainability initiatives will also discover practical solutions to address the pressing challenges.

World Energy Resources is an explanatory energy survey of the countries and major regions of the world, their geographic and economic settings, and signif icant inter-relationships. This book attempts to combine several interacting energy themes that encompass a historical development, energy issues and forecasts, economic geography, environmental programs, and world energy use. The main thrust of this book -World Energy Resources - is based on princi ples of energy science, applied geology, geophysics, and other environmental sciences as they relate to the exploration, exploitation, and production of resources in this country and throughout the world. This work is an analysis of the United States (USA) and world oil, gas, coal, and alternative energy resources and their associated issues, forecasts, and related policy. This book could not have been attempted without a broad geological exposure and international ge ographic awareness. Much information is scattered among federal and state agencies, schools, and other institutions, and this book has attempted to com bine some of the vast information base. This attempt can only skim the infor mation surface at best, but its regional and topical coverage is broad in scope. Part I introduces conventional energy resources and their historical develop ments, and includes chapters 1 to 7. The basic concepts and supporting facts on energy sources are presented here for the general education of energy analysts, policy makers, and scientists that desire a brief review of advanced technologies and history.

This book presents a collection of high-quality research papers accepted to multi-conference consisting of International Conference on Image Processing and Communications (IP&C 2021), International Conference on Computer Recognition Systems (CORES 2021), International Conference on Advanced Computer Systems (ACS 2021) held jointly in Bydgoszcz, Poland (virtually), in June 2021. The accepted papers address current computer science and computer systems-related technological challenges and solutions, as well as many practical applications and results. The first part of the book deals with advances in pattern recognition and classifiers, the second part is devoted to image processing and computer vision, while the third part addresses practical applications of computer recognition systems. Machine learning solutions for security and networks are tackled in part four of the book, while the last part collects papers on progress in advanced computer systems. We believe this book will be interesting for researchers and practitioners in many fields of computer science and IT applications.

This book constitutes the refereed proceedings of the Third International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2021. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cybersecurity. This book aims to develop an understanding of image processing, networks, and data modeling by using various machine learning algorithms for a wide range of real-world applications. In addition to providing basic principles of data processing, this book teaches standard models and algorithms for data and image analysis.