Focuses on the implementation of effective wastewater treatment with orientation towards biological processes Covers both biological and physico-chemical waste and wastewater treatment processes, focusing on emerging techniques Reviews computational method approaches, the application of TiO2-doped biopolymers, iron nanoparticles and the use of molecular techniques for wastewater treatment Illustrates molecular docking, molecular dynamics simulation, homology modeling, and biodegradation pathways prediction Includes dedicated chapters on biological wastewater treatment

The development of intelligent transportation systems has become significant in marine engineering especially Autonomous Underwater Vehicles with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including study of experimental investigation combined with hydrodynamic characteristics backed my MATLAB® codes and simulation study results. Features: Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. Evaluates performance of particle swarm intelligent based optimization techniques. Reviews propulsion performance of the remoted control vehicles based on machine learning techniques. Includes MATLAB® examples and simulation study results. This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.

Recent Advancement of IoT Devices in Pollution Control and Health Applications covers current developments in Internet of Things (IoT)-based pollution control, solid waste management, transportation, and healthcare systems. Because of its effects on physical and biological entities of the environment, the issue of environmental pollution and action has become a global concern. This guide highlights how environmental and health data from connected devices can be stored, analyzed, and eventually used-from developing indices for the state of environmental pollution, to diagnosing and treating patients and the role of IoT-based technology for pollution control.

This book focuses on industrial wastes that either join the streams or other natural water bodies directly, or are emptied into the municipal sewers, and their characteristics vary widely depending on the source of production and the raw material used by the industry, even during pre-industrial, industrial period and prospect of wastewater treatment for water resource conservation. The treatment of industrial wastewater can be done in part or as a whole either by the biological or chemical processes. Advanced treatment methods like membrane separation, ultra-filtration techniques and adsorption are elaborated. It would emphasize and facilitate a greater understanding of all existing available research, i.e., theoretical, methodological, well-established and validated empirical work, associated with the environment and climate change aspects.

This book covers the sustainability issues of a green environment towards economics and society in terms of alteration in industrial pollution levels, effect of reduced carbon emissions, changes in water bodies characteristics with respect to heavy metal contamination, monitoring of associated impact with respect to ecology and biodiversity, impact of reduced noise levels and air quality influences on human health, handling and management of biomedical waste. According to WHO, 80% of people living in urban areas are exposed to air exceeding safe limits. The advent of "sustainability in development science has led planners to apply evolving notions of "sustainability to the contemporary debate over how cities and regions should be revitalized, redeveloped, and reformed. Market allocation of resources, sustained levels of growth and consumption, an assumption that natural resources are unlimited and a belief that economic growth will "trickle down to the poor have been its hallmarks. The recent advance technology helps to promote green and clean modern societies continuously. The Internet of things will be playing an important role in the upcoming years in environment protection and sustainable development. There is a focus on paradigm shift in the sustainable development for the green environment during the period of isolation of COVID-19. This is the moment for the mobilization against the climate crisis. The sudden fall in pollutants and subsequent blue skies signifies a dramatic shift for India and also other affected countries during this period. Fighting climate change requires a collaborative approach between all spheres of society unlike the former. It must heavily redirect resources towards local, sustainable activities, including education, health, sustainable agriculture and circular management of resources. The impact of COVID-19 pandemic which has resulted in the dramatic change in the different aspects of the environment. The global lockdown has led to a rejuvenation of nature, ecosystems, biodiversity. Even urban environments are discovering a degree of peace and serenity, which led to decrease in greenhouse gas emission.

This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis, biometric, networking, manufacturing, data science, automation in electronics industries, and many more relevant fields. Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts, as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections: In this book on multimedia data engineering and machine learning, the reader will learn how to prepare inputs, interpret outputs, appraise discoveries, and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the the use of various machine learning algorithms, neural network algorithms, evolutionary techniques, fuzzy logic techniques, and deep learning techniques through projects, so that reader can easily understand, not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts, ideas, paradigms, tools, methodologies, and strategies that span both supervised and unsupervised engineering, with a particular emphasis on multimedia data engineering. The authors also emphasize the need of developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems, healthcare, security, finance, and economics, among others. Finally the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner. The primary users for the book include undergraduate, and postgraduate students, researchers, academicians, specialists, and practitioners in Computer Science and Engineering.