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Full Description
What are the means to create a paradigm shift from conventional to intelligent companies? Industry 6.0: Technology, Practices, Challenges and Applications shows how integrating Industry 6.0 technology with data creates a framework for that shift. The book discusses the limitations, pitfalls, and open research questions in Industry 6.0, as well as the most recent advances, architectures, frameworks, applications, and novel practices, methods, and techniques. These are vital for resolving intelligent Internet of Things issues. There is a special focus on sustainable growth, humanization and environmentally friendly intelligent system applications, and an emphasis on the latest innovations in intelligent systems in classical machine learning, deep learning, Internet of Things (IoT), Industrial Internet of Things (IIoT), blockchain, knowledge representation, knowledge management, big data, and natural language processing (NLP).
Features:
Presents the latest trends in the fields of intelligent systems, machine intelligence, deep learning, and Industrial Internet of Things for smart environments.
Discusses securing the mobile ad hoc network (MANET) by detecting the Intrusions using CSO and XGBoost model.
Highlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domains.
Focuses on intelligent process manufacturing, automation using robotics, development of robotic appliances, and smart manufacturing.
Covers data-driven agriculture, crop disease prediction, drip irrigation systems, pesticide and fertilizer sprinkling using the Industrial Internet of Things, and water estimation systems.
With many contemporary articles from both scientists and practitioners working in many fields where intelligent systems and the IIoT can break new ground, the text is assembled to aim at a readership that includes researchers, statisticians, practitioners, scientists, and developers.
Contents
1. Exploring the Synergy of IIoT, AI, and Data Analytics in Industry 6.0. 2. Artificial Intelligence and Machine Learning in Industry 6.0. 3. Big Data Fusion with GEN AI Tools: Driving Industry 6.0 Advancements. 4. Aerometamorphosis in Industry 6.0: Pioneering Structural Adaptability in Contemporary Aviation using Deep Learning. 5. Industry 6.0 in Transportation Systems: Exploring the Simulated Futures of Automated Bus Fleet Integration with Alternative Fuel Infrastructures in Closed Socio technical Environments. 6. Enhanced Deep Learning Networks for Advanced Intrusion Detection and Prevention Systems. 7. Using the Fuzzy Analytical Hierarchal Process for Selecting a Closed Socio technical Environment for Autonomous Vehicles Testing in the World of Industry 6.0. 8. ScatterNet based IPOA for predicting violent individuals using Real-time drone surveillance system. 9. An Optimal Framework for Intelligent Machine Learning-Based Early Diagnosis of Pre-Diabetes And Type-2 Diabetes Using Genomic Data. 10. DiabalanceML: Enhancing Diabetes Detection Performance through Dataset Balancing Strategies. 11. Identification of Earth Quake Patterns for Predictive Modeling using Decision Tree Classifiers to maintain Sustainability.
