Handbook of Research on Real-time Applications of Machine Learning in Cyber-physical Systems (Advances in Computational Intelligence and Robotics)

"This research book deals with real time applications of machine learning in cyber physical systems, for those who are working in the areas of machine learning approaches for CPS, the Internet of Things (IoT), and CPS and multidisciplinary applications of ML for CPS in the real world"-- Provided by publisher Cover Title Page Copyright Page Book Series Editorial Advisory Board Table of Contents Detailed Table of Contents Foreword Preface Acknowledgment Chapter 1: A Survey on Automotive Cyber-Physical Systems Chapter 2: Cyber Physical Systems Emergence With Reference to Manpower Development Chapter 3: Machine Learning in Cyber Physical Systems for Agriculture Chapter 4: Differential Privacy Techniques-Based Information Security for Cyber Physical System Applications Chapter 5: Machine Learning in Cyber Physical Systems for Healthcare Chapter 6: Application of Odd-Even Congruence Graph Labeling in Secured Cyber Physical Systems Chapter 7: Machine Learning for Intrusion Detection Systems Chapter 8: Estimating the Efficiency of Machine Learning Algorithms in Predicting Seizure With Convolutional Neural Network Architecture Chapter 9: Crop Protection Using Cyber Physical Systems and Machine Learning for Smart Agriculture Chapter 10: Arrhythmia Classification Using Deep Learning Architecture Chapter 11: Comparing Machine Learning Algorithms and DNN for Anomaly Detection Chapter 12: Vascular Disease Prediction Using Retinal Image Acquisition Algorithm Chapter 13: Convolutional Neural Network-Based Secured Data Storage Mechanism for Big Data Environments Chapter 14: CluniacChain Chapter 15: A Cyber Physical System Framework for Industrial Predictive Maintenance Using Machine Learning Compilation of References About the Contributors Index Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians. Discusses forensic accounting techniques and explores how forensic accountants add value while investigating claims of fraud. The book also highlights the corporate benefits of a forensic accounting audit and the acceptance of this evidence in a court of law.