Offering a comprehensive overview of the challenges, risks and options facing the future of mechatronics, this book provides insights into how these issues are currently assessed and managed. Building on the previously published book ‘Mechatronics in Action,’ it identifies and discusses the key issues likely to impact on future mechatronic systems. It supports mechatronics practitioners in identifying key areas in design, modeling and technology and places these in the wider context of concepts such as cyber-physical systems and the Internet of Things. For educators it considers the potential effects of developments in these areas on mechatronic course design, and ways of integrating these. Written by experts in the field, it explores topics including systems integration, design, modeling, privacy, ethics and future application domains. Highlighting novel innovation directions, it is intended for academics, engineers and students working in the field of mechatronics, particularly those developing new concepts, methods and ideas.

Mechatronics in Action’s case-study approach provides the most effective means of illustrating how mechatronics can make products and systems more flexible, more responsive and possess higher levels of functionality than would otherwise be possible. The series of case studies serves to illustrate how a mechatronic approach has been used to achieve enhanced performance through the transfer of functionality from the mechanical domain to electronics and software. Mechatronics in Action not only provides readers with access to a range of case studies, and the experts’ view of these, but also offers case studies in course design and development to support tutors in making the best and most effective use of the technical coverage provided. It provides, in an easily accessible form, a means of increasing the understanding of the mechatronic concept, while giving both students and tutors substantial technical insight into how this concept has been developed and used.

In the modern and data-driven business landscape, organizations face an increasingly complex challenge: how to harness the power of Artificial Intelligence (AI) and digital twin technology to stay competitive and relevant. This challenge is exacerbated by the rapid evolution of these technologies and the urgent need for businesses to adapt. AI continues to advance in areas such as language comprehension, pattern recognition, decision-making, and experiential learning, while digital twins are transforming into electronic replicas of real-world entities. Consequently, businesses grapple with the complexities of navigating this transformative convergence. Digital Twin Technology and AI Implementations in Future-Focused Businesses addresses the pressing issue of how AI and digital twin technology are altering the very fabric of business operations. It delves into the profound implications for productivity, creativity, and decision-making in organizations across diverse industries. Staying ahead of the technical curve is crucial, and this book equips readers with the knowledge and insights needed to thrive in this evolving business landscape.

BUILDING FUTURES An approach to Information Modeling engaging concepts of equality, sustainability, and labor as they relate to environment and architectural practice Building Futures: Technology, Ecology, and Architectural Practice explores how architects, and the buildings and environments we create, can engage future realities, both abstract and readily understood. These range from climate change and public health to advanced ideas about manufacture and construction. The text demonstrates multiple and hybrid paths in which building information modeling (BIM) and outgrowth technological processes including environmental simulation and human-robot interaction can be utilized in today’s contemporary context, expanding the architect’s agency by focusing on a more conceptual, and ecological, basis for our work. Moving beyond a basic understanding of the role of computation in architecture and design, the work shows how to think critically and speculatively about technology’s deeper and more lasting impacts on both architecture and society. Topics covered in Building Futures include: Technology: information modeling and the relationship between computational and real objects, new approaches to coding in architectural design, and direct-to-manufacture workflows Environment: understanding part-to-whole relationships at a variety of scales and the interconnectedness of things, post-subjective architectural approaches to ecology, and new ideas about sustainability Practice: revisiting architecture by remote control in the time of new global challenges, and novel ideas about creativity, authorship, and professionalism Design professionals and practice leaders grappling with the relationship of technology to design pedagogy will use Building Futures to better theorize and execute their architectural vision. Students in upper-level courses studying technique and theory will also find value in the work, which prepares incoming professionals for the major changes that the Architecture, Engineering, and Construction (AEC) industry may undergo in the coming years and decades. “The book prompts us to consider simulating events where architecture and architects could mitigate, redirect or develop contingencies, in relation to the environment, flows of material and capital, and other “things” that operate from the immediate, through to almost geological timescales.” From the Foreword by Robert Stuart-Smith, Director of the Autonomous Manufacturing Lab, University of Pennsylvania

This book presents the latest research on mechatronic systems engineering. By bringing together the most important papers from the 2018 Mechatronics Forum Conference ‘Reinventing Mechatronics,’ it outlines key trends in research and applications that will define mechatronics for the next 50 years. Mechatronics was established as an engineering discipline over 50 years ago, as the integration of electronics and information technology with mechanical design. Given major technological advances and the growth of systems-level concepts such as Cyber-Physical Systems and the Internet of Things, along with Cloud Technologies and Big Data, it’s now high time to reconsider the role of mechatronics, particularly within engineering design. Past and ongoing technological changes are impacting how systems are designed and configured in ways that could never have been envisaged when the field of mechatronics was first introduced.

Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science mainly focuses on the techniques of artificial intelligence (AI), Internet of Things (IoT) and data science for future communications systems. The goal of AI, IoT and data science for future communications systems is to create a venue for industry and academics to collaborate on the development of network and system solutions based on data science, AI and IoT. Recent breakthroughs in IoT, mobile and fixed communications and computation have paved the way for a data‐centric society of the future. New applications are increasingly reliant on machine‐to‐machine connections, resulting in unusual workloads and the need for more efficient and dependable infrastructures. Such a wide range of traffic workloads and applications will necessitate dynamic and highly adaptive network environments capable of self‐optimization for the task at hand while ensuring high dependability and ultra‐low latency. Networking devices, sensors, agents, meters and smart vehicles/systems generate massive amounts of data, necessitating new levels of security, performance and dependability. Such complications necessitate the development of new tools and approaches for providing successful services, management and operation. Predictive network analytics will play a critical role in insight generation, process automation required for adapting and scaling to new demands, resolving issues before they impact operational performance (e.g., preventing network failures and anticipating capacity requirements) and overall network decision‐making. To increase user experience and service quality, data mining and analytic techniques for inferring quality of experience (QoE) signals are required. AI, IoT, machine learning, reinforcement learning and network data analytics innovations open new possibilities in areas such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi‐agent systems and network ultra‐broadband deployment prioritization. These new analytic platforms will aid in the transformation of our networks and user experience. Future networks will enable unparalleled automation and optimization by intelligently gathering, analyzing, learning and controlling huge volumes of information.