Integrating Ai Techniques Into The Design And Development Of Smart Cyber Physical Systems
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Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems
Building on the knowledge of risks, vulnerabilities, and safety measures associated with cyber-physical systems, this book focuses on adapting artificial intelligence (AI) techniques to smart cyber-physical systems application development. The future is going to see cyber-physical systems in almost every aspect of life, so a book that focuses on shedding light on the design, development, and security aspects of cyber-physical systems in more crucial domains such as defense, healthcare, biomedical, smart city applications, is needed. Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems: Defense, Biomedical, Infrastructure, and Transportation offers an introductory exploration of the fundamental theories and concepts of AI and machine learning (ML) that are utilized in the building of dependable cyber-physical systems. It brings the ideas of advanced design and development and empowered security measures to cyber-physical systems. By focusing on the application of AI in cyber-physical systems design as well as security aspects, an improvement in reliability and advancements can be explored. Also included are the latest findings and advancements as well as case studies and illustrative examples on the design and development of smart cyber-physical systems. This resource is highly valuable for those employed in educational institutions, research laboratories, enterprises, and government agencies, as well as for students seeking novel ideas in the realm of smart cyber-physical systems design.
Integrating AI Techniques Into the Design and Development of Smart Cyber-Physical Systems
Integrating AI Techniques into the Design and Development of Smart Cyber-Physical Systems: Defense, Biomedical, Infrastructure, and Transportation offers an introductory exploration of the fundamental theories and concepts of Artificial Intelligence and Machine Learning utilized in the building of dependable cyber-physical systems.
Continuing Engineering Education for a Sustainable Future
Author: Patricia Caratozzolo
language: en
Publisher: Frontiers Media SA
Release Date: 2025-08-06
The World Economic Forum stated in its 2023 “Future of Jobs” report that 44% of workers' skills will change in the next five years. Additionally, six out of ten workers will require training before 2027, and only half will have adequate training opportunities. With this in mind, the three most pressing challenges currently facing the Continuing Engineering Education (CEE) community include: 1. The shifting skill requirements dictated by the job market. Engineering roles in various sectors are evolving, demanding a mix of Knowledge, Skills, and Abilities (KSA) that is difficult to predict with certainty. In addition, the pace of Digital Transformation will highly influence these requirements. 2. The climate change mitigation and adaptation. Engineers must reskill and adapt to changing sustainability requirements, and educational programs must support this transition. 3. The underrepresentation of minorities. Women, racial and ethnic minorities, and individuals with disabilities face disparities in opportunities, mentorship, and inclusion.