Machine learning (ML) and the internet of things (IoT) are the top technologies used by businesses to increase efficiency, productivity, and competitiveness in this fast-paced digital era transformation. ML is the key tool for fast processing and decision making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. IoT technology has proven efficient in solving many real-world problems, and ML algorithms combined with IoT means the fusion of product and intelligence to achieve better automation, efficiency, productivity, and connectivity. The Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries highlights the importance of ML for IoT’s success and diverse ML-powered IoT applications. This book addresses the problems and challenges in energy, industry, and healthcare and solutions proposed for ML-enabled IoT and new algorithms in ML. It further addresses their accuracy for existing real-time applications. Covering topics such as agriculture, pattern recognition, and smart applications, this premier reference source is an essential resource for engineers, scientists, educators, students, researchers, and academicians.

The text begins by highlighting the benefits of the Internet of Things-enabled machine learning in the healthcare sector, examines the diagnosis of diseases using machine learning algorithms, and analyzes security and privacy issues in the healthcare systems using the Internet of Things. The text elaborates on image processing implementation for medical images to detect and classify diseases based on magnetic resonance imaging and ultrasound images. This book: · Covers the procedure to recognize emotions using image processing and the Internet of Things-enabled machine learning. · Highlights security and privacy issues in the healthcare system using the Internet of Things. · Discusses classification and implementation techniques of image segmentation. · Explains different algorithms of machine learning for image processing in a comprehensive manner. · Provides computational intelligence on the Internet of Things for future biomedical applications including lung cancer. It is primarily written for graduate students and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and biomedical engineering.

In a world where business is increasingly influenced by rapid technological advancements and shifting societal norms, the definition of success has undergone a fundamental transformation. Profitability, once the sole measure of achievement, now shares the stage with sustainability as a critical component of business performance. As we transition into Society 5.0—a hyper-connected era where technology and human values converge—redefining success to include sustainability becomes not just desirable but essential. Sustainable Development, Humanities, and Social Sciences for Society 5.0 explores this paradigm shift, presenting a forward-thinking perspective on the intersection of technological innovation and sustainable business practices. This comprehensive volume bridges the gap between emerging technologies and the imperative for businesses to thrive in a way that benefits society and the environment. Through a curated collection of insights, strategies, and case studies, the book offers a valuable resource for understanding how to achieve continuous good performance while making a positive impact in the age of Society 5.0.

As the world grapples with pressing environmental challenges, the need for sustainable solutions has never been more urgent. From climate change to resource depletion, our planet faces unprecedented threats that require immediate action. Revolutionizing Automated Waste Treatment Systems: IoT and Bioelectronics emerge as a beacon of hope, offering comprehensive insights and practical guidance to address these critical issues. By delving into the principles and applications of green technologies, this book presents a roadmap towards a greener, more sustainable future. Recognizing the essential role that green technologies play in mitigating environmental degradation, this book emphasizes concepts such as smart technologies, bioelectronics, and the internet of things. It also illustrates how these innovations can be leveraged to create a more sustainable world. Readers will be educated on the importance of adopting these technologies, and the book provides actionable strategies for implementation. Use this impressive resource to grasp a more holistic approach to environmental sustainability, from designing green infrastructure to managing water resources.

In an age defined by the transformative ascent of cloud computing and the Internet of Things (IoT), our technological landscape has undergone a revolutionary evolution, enhancing convenience and connectivity in unprecedented ways. This convergence, while redefining how we interact with data and devices, has also brought to the forefront a pressing concern – the susceptibility of these systems to security breaches. As cloud services integrate further into our daily lives and the IoT saturates every aspect of our routines, the looming potential for cyberattacks and data breaches necessitates immediate and robust solutions to fortify the protection of sensitive information, ensuring the privacy and integrity of individuals, organizations, and critical infrastructure. Emerging Technologies for Securing the Cloud and IoT emerges as a comprehensive and timely solution to address the multifaceted security challenges posed by these groundbreaking technologies. Edited by Amina Ahmed Nacer from the University of Lorraine, France, and Mohammed Riyadh Abdmeziem from Ecole Nationale Supérieur d’Informatique, Algeria, this book serves as an invaluable guide for both academic scholars and industry experts. Its content delves deeply into the intricate web of security concerns, elucidating the potential ramifications of unaddressed vulnerabilities within cloud and IoT systems. With a pragmatic focus on real-world applications, the book beckons authors to explore themes like security frameworks, integration of AI and machine learning, data safeguarding, threat modeling, and more. Authored by esteemed researchers, practitioners, and luminaries, each chapter bridges the divide between theory and implementation, aiming to be an authoritative reference empowering readers to adeptly navigate the complexities of securing cloud-based IoT systems. A crucial resource for scholars, students, professionals, and policymakers striving to comprehend, confront, and surmount contemporary and future security challenges, this book stands as the quintessential guide for ushering in an era of secure technological advancement.

The academic community is currently facing the challenge of navigating the complexities of swarm robotics. This field demands understanding the design, control, and coordination of autonomous robotic swarms. The intricacies of developing algorithms that facilitate communication, cooperation, and adaptation among simple individual agents remain a formidable obstacle. Addressing issues like task allocation, formation control, path planning, and decentralized decision-making are pivotal to unlocking the true potential of swarm robotics. Bio-inspired Swarm Robotics and Control: Algorithms, Mechanisms, and Strategies immerses readers in the cutting-edge realm of swarm robotics, a discipline inspired by the intricate choreography observed in biological systems like insect colonies, bird flocks, and fish schools. Encompassing a rich array of bio-inspired algorithms, mechanisms, and strategies, the text elucidates how robots can communicate, cooperate, and adapt within dynamic environments. The book propels robotics, automation, and artificial intelligence advancements by fostering interdisciplinary connections and charting a course toward more efficient and resilient multi-robot systems. This book is ideal for biologists, engineers, and computer scientists to join forces in unlocking the full potential of swarm robotics.

Smart systems are rapidly evolving and finding ways to influence different aspects of human life, industry, and the environment. Smart systems based on available data should have the ability to predict and be adaptive, which leads to performing reliable, smart actions. Smartness and learning capabilities are essential characteristics describing smart systems besides connectivity and digital virtual cloudification technologies. Perspectives and Considerations on the Evolution of Smart Systems discusses the latest edge development that informs and facilitates the next level of development. It highlights how the evolving technologies and techniques are going to impact the developments in the field considering climate, environment, circular economy, and ecosystems. Covering topics such as dynamic difficulty adjustment, intelligent control, and serious games, this premier reference source is an excellent resource for engineers, computer scientists, IT professionals, developers, data analysts, students and educators of higher education, librarians, researchers, and academicians.

In the realm of analyzing human emotions through Artificial Intelligence (AI), a myriad of challenges persist. From the intricate nuances of emotional subtleties to the broader concerns of ethical considerations, privacy implications, and the ongoing battle against bias, AI faces a complex landscape when venturing into the understanding of human emotions. These challenges underscore the intricate balance required to navigate the human psyche with accuracy. The book, Using Machine Learning to Detect Emotions and Predict Human Psychology, serves as a guide for innovative solutions in the field of emotion detection through AI. It explores facial expression analysis, where AI decodes real-time emotions through subtle cues such as eyebrow movements and micro-expressions. In speech and voice analysis, the book unveils how AI processes vocal nuances to discern emotions, considering elements like tone, pitch, and language intricacies. Additionally, the power of text analysis is of great importance, revealing how AI extracts emotional tones from diverse textual communications. By weaving these systems together, the book offers a holistic solution to the challenges faced by AI in understanding the complex landscape of human emotions.