Decision-making is a frequent problem in today's financial, business, and industrial world. Thus, fuzzy expert systems are increasingly being used to solve decision-making problems by attempting to solve a part or whole of a practical problem. These expert systems have proven that they can solve problems in various domains where human expertise is required, including the field of agriculture. Fuzzy Expert Systems and Applications in Agricultural Diagnosis is a crucial source that examines the use of fuzzy expert systems for prediction and problem solving in the agricultural industry. Featuring research on topics such as nutrition management, sustainable agriculture, and defuzzification, this book is ideally designed for farmers, researchers, scientists, academics, students, policymakers, and development practitioners seeking the latest research in technological tools that support crop disease diagnosis.

There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these "game changers," governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society. This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation. The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.

Autism spectrum disorder (ASD) is known as a neuro-disorder in which a person may face problems in interaction and communication with people, amongst other challenges. As per medical experts, ASD can be diagnosed at any stage or age but is often noticeable within the first two years of life. If caught early enough, therapies and services can be provided at this early stage instead of waiting until it is too late. ASD occurrences appear to have increased over the last couple of years leading to the need for more research in the field. It is crucial to provide researchers and clinicians with the most up-to-date information on the clinical features, etiopathogenesis, and therapeutic strategies for patients as well as to shed light on the other psychiatric conditions often associated with ASD. In addition, it is equally important to understand how to detect ASD in individuals for accurate diagnosing and early detection. Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder discusses the early detection and diagnosis of autism spectrum disorder enabled by artificial intelligence technologies, applications, and therapies. This book will focus on the early diagnosis of ASD through artificial intelligence, such as deep learning and machine learning algorithms, for confirming diagnosis or suggesting the need for further evaluation of individuals. The chapters will also discuss the use of artificial intelligence technologies, such as medical robots, for enhancing the communication skills and the social and emotional skills of children who have been diagnosed with ASD. This book is ideally intended for IT specialists, data scientists, academicians, scholars, researchers, policymakers, medical practitioners, and students interested in how artificial intelligence is impacting the diagnosis and treatment of autism spectrum disorder.

The internet of things (IoT) is quickly growing into a large industry with a huge economic impact expected in the near future. However, the users' needs go beyond the existing web-like services, which do not provide satisfactory intelligence levels. Ambient intelligence services in IoT environments is an emerging research area that can change the way that technology and services are perceived by the users. Ambient Intelligence Services in IoT Environments: Emerging Research and Opportunities is a unique source that systemizes recent trends and advances for service development with such key technological enablers of modern ICT as ambient intelligence, IoT, web of things, and cyber-physical systems. The considered concepts and models are presented using a smart spaces approach with a particular focus on the Smart-M3 platform, which is now shaping into an open source technology for creating ontology-based smart spaces and is shifting towards the development of web of things applications and socio-cyber-physical systems. Containing coverage on a broad range of topics such as fog computing, smart environments, and virtual reality, multitudes of researchers, students, academicians, and professionals will benefit from this timely reference.

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

As digital technology continues to revolutionize the world, businesses are also evolving by adopting digital technologies such as artificial intelligence, digital marketing, and analytical methods into their daily practices. Due to this growing adoption, further study on the potential solutions modern technology provides to businesses is required to successfully apply it across industries. AI-Driven Intelligent Models for Business Excellence explores various artificial intelligence models and methods for business applications and considers algorithmic approaches for business excellence across numerous fields and applications. Covering topics such as business analysis, deep learning, machine learning, and analytical methods, this reference work is ideal for managers, business owners, computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Food is a necessary aspect of human life, and agriculture is crucial to any country's global economy. Because the food business is essential to both a country's economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.

Artificial intelligence has become an invaluable tool in modern society and can be utilized across fields such as healthcare, travel, education, and construction. There are numerous benefits for companies, industries, and governments when adopting this technology into their daily operations as it continues to evolve to support the needs of society. Further study on the challenges and strategies of implementation is required in order to ensure the technology is employed to its full potential. Artificial Intelligence for Societal Development and Global Well-Being considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. Covering a range of topics such as smart devices, artificial neural networks, and natural intelligence, this reference work is crucial for scientists, librarians, business owners, government officials, entrepreneurs, scholars, researchers, practitioners, instructors, and students.

Increased use of artificial intelligence (AI) is being deployed in many hospitals and healthcare settings to help improve health care service delivery. Machine learning (ML) and deep learning (DL) tools can help guide physicians with tasks such as diagnosis and detection of diseases and assisting with medical decision making. This edited book outlines novel applications of AI in e-healthcare. It includes various real-time/offline applications and case studies in the field of e-Healthcare, such as image recognition tools for assisting with tuberculosis diagnosis from x-ray data, ML tools for cancer disease prediction, and visualisation techniques for predicting the outbreak and spread of Covid-19. Heterogenous recurrent convolution neural networks for risk prediction in electronic healthcare record datasets are also reviewed. Suitable for an audience of computer scientists and healthcare engineers, the main objective of this book is to demonstrate effective use of AI in healthcare by describing and promoting innovative case studies and finding the scope for improvement across healthcare services.

Emerging technologies continue to affect a variety of industries, making processes more effective and efficient. However, they also impact society by promoting opportunities to encourage social change and socioeconomic advancement. Blockchain is one that is already influencing third world countries and disrupting the globe. Blockchain Technology for Global Social Change is an essential research publication that provides insight into advancements being made in blockchain and some potential applications of the technology that can improve the lives of individuals in emerging markets. This publication covers a range of topics such as digital government, health systems, and urbanization and is ideal for policymakers, academicians, researchers, sociologists, government officials, economists, and financial experts seeking current and relevant research on evolving blockchain technologies.

In this book, translated into English for the first time, Lelio Demichelis takes on a modern perspective of the concept/process of alienation. This concept-much more profound and widespread today than first described and denounced by Marx-has largely been forgotten and erased. Using the characters of Narcissus, Pygmalion and Prometheus, the author reinterprets and updates Marx, Nietzsche, Anders, Foucault and, in particular, critical theory and the Frankfurt School views on an administered society (where everything is automated and engineered, manifest today in algorithms, AI, machine learning and social networking) showing that, in a world where old and new forms of alienation come together, man is increasingly led to delegate (i.e. alienate) sovereignty, freedom, responsibility and the awareness of being alive.

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.

Autonomic networking aims to solve the mounting problems created by increasingly complex networks, by enabling devices and service-providers to decide, preferably without human intervention, what to do at any given moment, and ultimately to create self-managing networks that can interface with each other, adapting their behavior to provide the best service to the end-user in all situations. This book gives both an understanding and an assessment of the principles, methods and architectures in autonomous network management, as well as lessons learned from, the ongoing initiatives in the field. It includes contributions from industry groups at Orange Labs, Motorola, Ericsson, the ANA EU Project and leading universities. These groups all provide chapters examining the international research projects to which they are contributing, such as the EU Autonomic Network Architecture Project and Ambient Networks EU Project, reviewing current developments and demonstrating how autonomic management principles are used to define new architectures, models, protocols, and mechanisms for future network equipment.

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.

The advent of Artificial Intelligence (AI) as an "autonomous author" urges the law to rethink authorship, originality, creativity. AI-generated artworks are in search of an author because current copyright laws offer as a solution only public domain or fragile regulatory mechanisms. During the 20th century visual artists have been posing persistent challenges to the law world: Conceptual Art favoured legal mechanisms alternative to copyright law. The case of AI-art is, however, different: for the first time the artworld is discovering the prospective of an art without human authors. Rather than preserving the status quo in the law world, policy makers should consider a reformative conception of AI in copyright law and take inspiration from innovative theories in the field of robot law, where new frames for a legal personhood of artificial agents are proposed. This would have a spill-over effect also on copyright regulations.

Ongoing advancements in modern technology have led to significant developments with smart technologies. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Smart Technologies: Breakthroughs in Research and Practice provides comprehensive and interdisciplinary research on the most emerging areas of information science and technology. Including innovative studies on image and speech recognition, human-computer interface, and wireless technologies, this multi-volume book is an ideal source for researchers, academicians, practitioners, and students interested in advanced technological applications and developments.

Quantum Inspired Computational Intelligence: Research and Applications explores the latest quantum computational intelligence approaches, initiatives, and applications in computing, engineering, science, and business. The book explores this emerging field of research that applies principles of quantum mechanics to develop more efficient and robust intelligent systems. Conventional computational intelligence-or soft computing-is conjoined with quantum computing to achieve this objective. The models covered can be applied to any endeavor which handles complex and meaningful information.