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Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. - Introduces novel intelligent techniques needed to address environmental pollution for the well-being of the global environment - Offers perspectives on the design, development and commissioning of intelligent applications - Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies surrounding the monitoring and mitigation of environmental pollution - Puts forth insights on future generation intelligent pollution monitoring techniques
Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering merges computer engineering and environmental engineering. The book presents the latest finding on how data science and AI-based tools are being applied in environmental engineering research. This application involves multiple domains such as data science and artificial intelligence to transform the data collected by intelligent sensors into relevant and reliable information to support decision-making. These tools include fuzzy logic, knowledge-based systems, particle swarm optimization, genetic algorithms, Monte Carlo simulation, artificial neural networks, support vector machine, boosted regression tree, simulated annealing, ant colony algorithm, decision tree, immune algorithm, and imperialist competitive algorithm. This book is a fundamental information source because it is the first book to present the foundational reference material in this new research field. Furthermore, it gives a critical overview of the latest cross-domain research findings and technological developments on the recent advances in computer-aided intelligent environmental data engineering. Captures the application of data science and artificial intelligence for a broader spectrum of environmental engineering problems Presents methods and procedures as well as case studies where state-of-the-art technologies are applied in actual environmental scenarios Offers a compilation of essential and critical reviews on the application of data science and artificial intelligence to the entire spectrum of environmental engineering
This book presents an overview of modeling and simulation of environmental systems via diverse research problems and pertinent case studies. It is divided into four parts covering sustainable water resources modeling, air pollution modeling, Internet of Things (IoT) based applications in environmental systems, and future algorithms and conceptual frameworks in environmental systems. Each of the chapters demonstrate how the models, indicators, and ecological processes could be applied directly in the environmental sub-disciplines. It includes range of concepts and case studies focusing on a holistic management approach at the global level for environmental practitioners. Features: Covers computational approaches as applied to problems of air and water pollution domain. Delivers generic methods of modeling with spatio-temporal analyses using soft computation and programming paradigms. Includes theoretical aspects of environmental processes with their complexity and programmable mathematical approaches. Adopts a realistic approach involving formulas, algorithms, and techniques to establish mathematical models/computations. Provides a pathway for real-time implementation of complex modeling problem formulations including case studies. This book is aimed at researchers, professionals and graduate students in Environmental Engineering, Computational Engineering/Computer Science, Modeling/Simulation, Environmental Management, Environmental Modeling and Operations Research.
Resource Recovery in Drinking Water Treatment concentrates on techniques and methods for water purification. The book develops a new approach—resource recovery—toward drinking water, including the role of methods (adsorption, membrane, ion – exchange, biosorption, coagulation, etc.) and nanocomposites (such as biochar, sludge-based composites, chitosan, polymer, magnetic particles, etc.) in water resource recovery. It provides an in-depth overview on emerging water treatment techniques and the resource recovery of materials during the treatment process. Finally, the book aims to introduce polluted waters as new and sustainable sources rather than seeing wastewaters only a source of hazardous organic and inorganic matters. This book is part of a three-volume set that stresses the importance of contaminated water remediation, including surface waters, municipal or industrial wastewaters, and waters as a new source of nutrients, minerals and energy. Presents novel approaches to recover materials from water during treatment Discusses fundamentals and principals of water treatment to figure out current status and need for new development Includes applications of various composites and particles in water treatment and water recovery
This book includes a general overview of the book series and summarizes the research results in its 13 subtopics. It systematically elaborates on how the construction and promotion of intelligent cities with Chinese characteristics could be implemented in the course of intelligent urbanization in China. Furthermore, it presents a variety of literature on urban management innovation and development, making it a valuable reference source on both the theoretic and empirical development of the new urbanization in China for intelligent-city decision-makers, c-level directors and officials in urban economy, social and environment departments and institutions all over the world.
Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. - Presents tools, connections and proactive solutions to take sustainability programs to the next level - Offers a practical guide for making students proficient in modern electronic data analysis and graphics - Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery
Advances in Yeast Biotechnology for Biofuels and Sustainability: Value-Added Products and Environmental Remediation Applications showcases the uses for engineered yeast in environmental applications, especially as an innovative source of biofuels. Beginning with a thorough review of recent advances and future potential for yeast biotechnology, the book proceeds to outline several options for biofuels, including lignocellulosic biofuels and alternative feedstock production through hydrolysis and alternative value-added products, including industrial acids and bioplastics and applications in agriculture and environmental remediation. Placing case studies at the center of each chapter, this book presents a future-focused perspective on the potential of yeast biotechnologies to support sustainability. - Lays out methods, including multiple options for generating biofuels from engineered yeast and several additional value-added products - Presents a wide variety of real-world sustainable applications for engineered yeast, with a focus on biofuels production - Provides a selection of case studies in other value-added products and applications, including bioremediation, pollution remediation, and biofertilizers in sustainable agriculture