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This book explores the intersection of the Internet of Things (IoT) and Artificial Intelligence (AI) in sustaining a green environment, sustainable societies, and thriving industries. It offers a comprehensive exploration of how these technologies intersect and transform various sectors to enhance environmental conservation, societal well-being, and industrial progress. The book features a diverse array of case studies, methodologies, and notes on technological advancements. Readers will gain valuable insights into the impact of AI and IoT on sustainable initiatives through real-world examples, research findings, and discussions on future directions. Key themes AI in complex and versatile scenarios: Chapters 1 and 4 explore AI applications in combatant identification and COVID-19 monitoring IoT for efficiency and data-driven decision-making: Chapters 2, 3, and 7 focus on IoT implementations in battery monitoring for electric vehicles, healthcare systems, and precision farming AI for diagnostics and computer vision: Chapters 5, 9, and 13 highlight AI-driven solutions for plant disease detection, fetal spine disorder detection, and defect detection Industry applications: Chapters 6, 8, 10, 11, 12, 14, 15, 16, and 17 cover AI and IoT in healthcare, transportation, supply chain management, endangered species protection, crop management, and pollution detection, showcasing their transformative potential across various domains. This book is ideal for readers with multidisciplinary backgrounds, including researchers, academics, professionals, and students interested in IoT, AI, environmental sustainability, healthcare, agriculture, smart technologies, and industrial innovation.
Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods. - Focuses on recent research in mathematics applications for Industry 4.0 - Provides insights on international and transnational scales - Identifies mathematics knowledge gaps for Industry 4.0 - Describes fruitful areas for further research in industrial mathematics, including forthcoming international studies and research
Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.
- Collection of results of multicriteria optimization, including nonlinear, linear and combinatorial optimization problems - Includes numerous illustrations, examples and problems
Evolution and Trends of Sustainable Approaches: Latest Development and Innovations in Science and Technology Applications provides different trends and approaches within the sustainability framework to assess their impact and offer possible solutions to problems facing the global sustainability paradigm. This book evaluates sustainability assessment approaches which support different levels of both decision-making and policy processes, thereby improving the management of natural and human systems. This book explores sustainable firm solutions, the upward trend of sustainability, and its variants. At the same time, different existing approaches are analyzed. These sustainable assessment approaches can be applied to products, services and technologies as well as business models, such as the Product-Service-System (PSS), Circular Economy (CE), Industrial Symbiosis (IS), and Supply Chain (SC). Finally, the book explores Sustainability Indicators (SIs), which are widely used to measure and communicate progress towards sustainable development, along with Life Cycle Sustainability Assessment (LCSA), balancing the three dimensions of sustainability (environmental, social and economic). - Explores innovative strategies and advanced trends of sustainable approaches, engineering, and industrial applications - Analyzes sustainability assessments and their role in planning and project processes - Reviews state-of-the-art sustainable technologies - Evaluates approaches for organizations to achieve both sustainability assessment and sustainable solutions
This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.
With increasing global concerns toward environmental protection and sustainable development, green supply chain management (GSCM) has drawn much attention from academicians and practitioners. Selecting an optimal green supplier is a critical part of GSCM, which can be viewed as a kind of multi-criteria decision making (MCDM) problem. To derive the best result, large group of decision makers are often involved in the green supplier selection nowadays. Besides, decision makers tend to express their evaluations utilizing uncertain linguistic terms due to the vagueness of human thinking. Hence, this paper aims to propose a hybrid MCDM approach for green supplier selection within the large group setting. More concretely, interval-valued intuitionistic uncertain linguistic sets (IVIULSs) are applied for assessing the performance of green suppliers concerning each criterion. Ant colony algorithm is utilized to cluster decision makers into several subgroups. The linear programming technique for multidimensional analysis of preference (LINMAP) is adopted for the determination of the optimal weights of criteria objectively. Finally, an extended MULTIMOORA approach is utilized to generate the ranking of alternative suppliers. The practicality and usefulness of the developed large group green supplier selection framework is illustrated using an empirical example of a real estate company.
Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.