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The 15th international conference interdisciplinarity in engineering : conference proceedings / / edited by Liviu Moldovan and Adrian Gligor
| The 15th international conference interdisciplinarity in engineering : conference proceedings / / edited by Liviu Moldovan and Adrian Gligor |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (869 pages) |
| Disciplina | 658.4038028563 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Production engineering
Computational intelligence Industry 4.0 |
| ISBN | 3-030-93817-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910522558503321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Africa and the fourth Industrial Revolution : curse or cure? / / Everisto Benyera, editor
| Africa and the fourth Industrial Revolution : curse or cure? / / Everisto Benyera, editor |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (163 pages) |
| Disciplina | 658.4038028563 |
| Collana | Advances in African economic, social and political development |
| Soggetto topico |
Industry 4.0 - Africa
Industry 4.0 |
| ISBN | 3-030-87524-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523781003321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Architecture and Design for Industry 4.0 : Theory and Practice / / edited by Maurizio Barberio, Micaela Colella, Angelo Figliola, Alessandra Battisti
| Architecture and Design for Industry 4.0 : Theory and Practice / / edited by Maurizio Barberio, Micaela Colella, Angelo Figliola, Alessandra Battisti |
| Autore | Barberio Maurizio |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (961 pages) |
| Disciplina | 658.4038028563 |
| Altri autori (Persone) |
ColellaMicaela
FigliolaAngelo BattistiAlessandra |
| Collana | Lecture Notes in Mechanical Engineering |
| Soggetto topico |
Industrial engineering
Production engineering Computer-aided engineering Building information modeling Internet of things Industrial and Production Engineering Computer-Aided Engineering (CAD, CAE) and Design Building Information Modeling Internet of Things |
| ISBN | 3-031-36922-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The big vision: from Industry 4.0 to 5.0 for a new AEC sector -- Achieving SDGs in Industry 4.0. Between performance-oriented digital design and circular economy -- Industry 4.0 for AEC sector: impacts on productivity and sustainability -- Programming Design Environments to Foster Human-Machine Experiences -- Designing with the chain -- Adauctus Architectus Novus on the definition of a new professional figure -- Lotus Aeroad - Pushing the Scale of Tensegrity Structures -- Unlocking Spaces for Everyone -- Parameterization and Mechanical Behavior of Multi-Block Columns. |
| Record Nr. | UNINA-9910760265603321 |
Barberio Maurizio
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence and Cyber Security in Industry 4.0 [[electronic resource] /] / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi
| Artificial Intelligence and Cyber Security in Industry 4.0 [[electronic resource] /] / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi |
| Autore | Sarveshwaran Velliangiri |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (374 pages) |
| Disciplina | 658.4038028563 |
| Altri autori (Persone) |
ChenJoy Iong-zong
PelusiDanilo |
| Collana | Advanced Technologies and Societal Change |
| Soggetto topico |
Artificial intelligence
Internet of things Big data Machine learning Computational intelligence Wireless communication systems Mobile communication systems Artificial Intelligence Internet of Things Big Data Machine Learning Computational Intelligence Wireless and Mobile Communication |
| ISBN | 981-9921-15-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Artificial Intelligence and Cyber Security for Industry -- Role of AI and its impact on the development of cyber security applications -- AI and IoT in Manufacturing and related Security Perspectives for Industry 4.0 -- IoT Security Vulnerabilities and Defensive Measures in Industry 4.0 -- Adopting Artificial Intelligence in ITIL for Information Security Management - Way forward in Industry 4.0 -- Intelligent Autonomous Drones in Industry 4.0 -- A review on automatic generation of attack trees and its application to automotive cybersecurity -- Malware Analysis using Machine Learning Tools and Techniques in IT Industry -- USE OF MACHINE LEARNING IN FORENSICS AND COMPUTER SECURITY -- Control of feed drives in CNC machine tools using artificial immune adaptive strategy -- Efficient Anomaly Detection for Empowering Cyber Security by Using Adaptive Deep Learning Model -- Intrusion Detection in IoT based Healthcare Using ML and DL approaches: A Case Study -- War Strategy Algorithm based GAN model for Detecting the Malware Attacks in Modern Digital Age -- ML algorithms for providing financial security in banking sectors with the prediction of loan risks -- Machine Learning based DDoS Attack Detection using Support Vector Machine -- Artificial Intelligence based Cyber Security Applications. |
| Record Nr. | UNISA-996546840703316 |
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Sarveshwaran Velliangiri
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Artificial Intelligence and Cyber Security in Industry 4.0 / / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi
| Artificial Intelligence and Cyber Security in Industry 4.0 / / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi |
| Autore | Sarveshwaran Velliangiri |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (374 pages) |
| Disciplina | 658.4038028563 |
| Altri autori (Persone) |
ChenJoy Iong-zong
PelusiDanilo |
| Collana | Advanced Technologies and Societal Change |
| Soggetto topico |
Artificial intelligence
Internet of things Big data Machine learning Computational intelligence Wireless communication systems Mobile communication systems Artificial Intelligence Internet of Things Big Data Machine Learning Computational Intelligence Wireless and Mobile Communication |
| ISBN | 981-9921-15-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Artificial Intelligence and Cyber Security for Industry -- Role of AI and its impact on the development of cyber security applications -- AI and IoT in Manufacturing and related Security Perspectives for Industry 4.0 -- IoT Security Vulnerabilities and Defensive Measures in Industry 4.0 -- Adopting Artificial Intelligence in ITIL for Information Security Management - Way forward in Industry 4.0 -- Intelligent Autonomous Drones in Industry 4.0 -- A review on automatic generation of attack trees and its application to automotive cybersecurity -- Malware Analysis using Machine Learning Tools and Techniques in IT Industry -- USE OF MACHINE LEARNING IN FORENSICS AND COMPUTER SECURITY -- Control of feed drives in CNC machine tools using artificial immune adaptive strategy -- Efficient Anomaly Detection for Empowering Cyber Security by Using Adaptive Deep Learning Model -- Intrusion Detection in IoT based Healthcare Using ML and DL approaches: A Case Study -- War Strategy Algorithm based GAN model for Detecting the Malware Attacks in Modern Digital Age -- ML algorithms for providing financial security in banking sectors with the prediction of loan risks -- Machine Learning based DDoS Attack Detection using Support Vector Machine -- Artificial Intelligence based Cyber Security Applications. |
| Record Nr. | UNINA-9910731481703321 |
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Sarveshwaran Velliangiri
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom / / edited by Amina Al-Marzouqi, Said A. Salloum, Mohammed Al-Saidat, Ahmed Aburayya, Babeet Gupta
| Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom / / edited by Amina Al-Marzouqi, Said A. Salloum, Mohammed Al-Saidat, Ahmed Aburayya, Babeet Gupta |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (655 pages) |
| Disciplina | 658.4038028563 |
| Collana | Studies in Big Data |
| Soggetto topico |
Engineering - Data processing
Computational intelligence Big data Data Engineering Computational Intelligence Big Data |
| ISBN | 3-031-52280-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Welcome to the Age of ChatGPT -- The Coming ChatGPT -- Exploring the Interpretability of Sequential Predictions through Rationale Model -- AI in Education: An Overview -- Adopting the Power of AI Chatbots for Enriching Students Learning in Civil Engineering Education: A Study on Capabilities and Limitations -- Revolutionizing Education of Art and Design through ChatGPT -- ChatGPT-Artificial Intelligence Studies of Business Analytics Adoption and Usage. |
| Record Nr. | UNINA-9910847074803321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational modelling in Industry 4.0 : a sustainable resource management perspective / / Irfan Ali [and four others] editors
| Computational modelling in Industry 4.0 : a sustainable resource management perspective / / Irfan Ali [and four others] editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (374 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico | Industry 4.0 |
| ISBN |
981-16-7722-0
981-16-7723-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743234503321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Digital Transformation in Industry : Trends, Management, Strategies / / edited by Vikas Kumar, Jafar Rezaei, Victoria Akberdina, Evgeny Kuzmin
| Digital Transformation in Industry : Trends, Management, Strategies / / edited by Vikas Kumar, Jafar Rezaei, Victoria Akberdina, Evgeny Kuzmin |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (290 pages) |
| Disciplina | 658.4038028563 |
| Collana | Lecture Notes in Information Systems and Organisation |
| Soggetto topico |
Business information services
Industries Application software Microeconomics IT in Business Enterprise Architecture Computer and Information Systems Applications |
| ISBN | 3-030-73261-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Industry 4.0: Individual perceptions about its nine technologies -- Industrial Policy: A New Reality in the Context of Digital Transformation of the Economy -- A Framework for Continuous Assessment of IT Value in Industry 4.0 -- Prerequisites and Principles of Digital Platformization of the Economy -- Modeling the digital transformation of the region’s industry -- Visual methodology for the multi-factor assessment of industrial digital transformation components -- Modeling the factors behind digitalization of the real sector of the economy -- Research on the impact of digital services on the economic performance of industrial enterprises -- Coverage of Production Chains in Cooperation Industrial Enterprises. |
| Record Nr. | UNINA-9910495200103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Electronics in advanced research industries : industry 4.0 to industry 5.0 advances / / Alessandro Massaro
| Electronics in advanced research industries : industry 4.0 to industry 5.0 advances / / Alessandro Massaro |
| Autore | Massaro Alessandro <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (538 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Industry 4.0
Electronics - Safety measures |
| ISBN |
1-119-71689-6
1-119-71690-X 1-119-71688-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- About the Author -- Chapter 1 State of the Art and Technology Innovation -- 1.1 State of the Art of Flexible Technologies in Industry -- 1.1.1 Sensors and Actuators Layer: I/O Layer -- 1.1.2 Agent/Firmware Layer: User Interface Layer -- 1.1.3 Gateway and Enterprise Service Bus Layer -- 1.1.4 IoT Middleware -- 1.1.5 Processing Layer -- 1.1.6 Application Layer -- 1.1.7 File Transfer Protocols -- 1.2 State of the Art of Scientific Approaches Oriented on Process Control and Automatisms -- 1.2.1 Architectures Integrating AI -- 1.2.2 AI Supervised and Unsupersived Algorithms -- 1.2.3 AI Image Processing -- 1.2.4 Production Process Mapping -- 1.2.5 Technologies of Industry 4.0 and Industry 5.0: Interconnection and Main Limits -- 1.2.6 Infrared Thermography in Monitoring Process -- 1.2.7 Key Parameters in Supply Chain and AI Improving Manufacturing Processes -- 1.3 Intelligent Automatic Systems in Industries -- 1.4 Technological Approaches to Transform the Production in Auto-Adaptive Control and Actuation Systems -- 1.5 Basic Concepts of Artificial Intelligence -- 1.6 Knowledge Upgrading in Industries -- References -- Chapter 2 Information Technology Infrastructures Supporting Industry 5.0 Facilities -- 2.1 Production Process Simulation and Object Design Approaches -- 2.1.1 Object Design of a Data Mining Algorithm: Block Functions and Parameter Setting -- 2.1.2 Example 1: BPM Modeling of Wheat Storage Process for Pasta Production -- 2.1.3 Example 2: Block Diagram Design of a Servo Valve Control and Actuation System -- 2.1.4 Example 3: Block Diagram of a Liquid Production System -- 2.1.5 Example 4: UML Design of a Programmable Logic Controller System -- 2.1.6 Example 5: Electronic Logic Timing Diagram -- 2.1.7 Example 6: AR System in Kitchen Production Process.
2.1.8 Example 7: Intelligent Canned Food Production Line -- 2.2 Electronic Logic Design Oriented on Information Infrastructure of Industry 5.0 -- 2.3 Predictive Maintenance: Artificial Intelligence Failure Predictions and Information Infrastructure Layout in the Temperature Monitoring Process -- 2.4 Defect Estimation and Prediction by Artificial Neural Network -- 2.4.1 Other Methodologies to Map and Read Production Failures and Defects -- 2.5 Defect Clustering and Classification: Combined Use of the K-Means Algorithm with Infrared Thermography for Predictive Maintenance -- 2.6 Facilities of a Prototype Network Implementing Advanced Technology: Example of an Advanced Platform Suitable for Industry 5.0 Integrating Predictive Maintenance -- 2.7 Predictive Maintenance Approaches -- 2.7.1 Preventive Maintenance and Predictive Maintenance Operations in the Railway Industry -- 2.8 Examples of Advanced Infrastructures Implementing AI -- 2.9 Examples of Telemedicine Platforms Integrating Advanced Facilities -- 2.9.1 Advanced Telecardiology Platform -- 2.9.2 Advanced Teleoncology Platform -- 2.9.3 Multipurpose E-Health Platform -- References -- Chapter 3 Human-Machine Interfaces -- 3.1 Mechatronic Machine Interface Architectures Integrating Sensor Systems -- 3.1.1 Multiple Mechatronic Boards Managing Different Production Stages -- 3.1.2 Mechatronic Boards Managing Component Processing -- 3.2 Machine-to-Machine Interfaces: New Concepts of Industry 5.0 -- 3.3 Production Line Command and Actuation Interfaces in Upgraded Systems -- 3.3.1 PLC, PAC, Industrial PC, and Improvements -- 3.3.2 SCADA Systems for Centralization of Data Production -- 3.4 McCulloch-Pitts Neurons and Logic Port for Automatic Decision-Making Setting Thresholds -- 3.5 Programmable Logic Controller I/O Ports Interfacing with AI Engine. 3.6 Human-Machine Interface for Data Transfer and AI Data Processing -- 3.7 Example of Interface Configuration of Temperature Control -- 3.8 AI Interfaces Oriented on Cybersecurity Attack Detection -- 3.9 AI Interfaces Oriented on Database Security -- 3.10 Cybersecurity Platform and AI Control Interface -- References -- Chapter 4 Internet of Things Solutions in Industry -- 4.1 Cloud Computing IoT -- 4.1.1 IoT Agent -- 4.1.2 IoT Gateway in Smart Environments -- 4.1.3 Basic Elements of a Smart Industry Environment Controlling Production -- 4.1.4 Augmented Reality Hardware and Cloud Computing Processing -- 4.1.5 Real-Time Control and Actuation -- 4.1.6 Localization Technologies in an Industrial Environment -- 4.1.7 GPU Processing Units -- 4.2 IoT and External Artificial Intelligence Engines -- 4.2.1 Artificial Engines and Server Location: Artificial Intelligence and Adaptive Production -- 4.2.2 IoT Security Systems in the Working Environment and Implementation Aspects -- 4.2.3 Example of Energy Power Control and Actuation: Energy Routing and Priority Load Management for Energy Efficiency -- 4.2.4 Online Configurators: Cloud DSS -- 4.3 Blockchain and IoT Data Storage Systems -- 4.3.1 Blockchain Implementation Rules -- 4.3.2 Blockchain and IoT Production Traceability -- 4.4 Mechatronic Machine Interface Architectures Integrating Sensor Systems -- 4.5 Multiple Mechatronic Boards Managing Different Production Stages -- References -- Chapter 5 Advanced Robotics -- 5.1 Collaborative Robotics in Industry and Protocols -- 5.1.1 Data Protocols -- 5.1.2 Basic Concepts of Robotic Arms and Control Improvement -- 5.1.3 Collaborative Exoskeleton Communication System Protocols -- 5.1.4 Advanced Robotics and Intelligent Automation in Manufacturing: Logic Conditions and PLC Programming -- 5.2 Artificial Intelligence in Advanced Robotics and Auto-Adaptive Movement. 5.2.1 General Technological Aspects about Auto-Adaptive Motion in Advanced Robotics -- 5.2.1.1 Main Aspects of Electrostatic Actuators -- 5.2.1.2 Microelectromechanical System Electrostatic Actuators -- 5.2.1.3 Piezoelectric Actuators -- 5.2.1.4 DC Motor Actuation -- 5.2.1.5 Intelligent Control Integrating AI: Speed Regulation -- 5.2.2 Improvement of Collaborative Exoskeletons by Auto-Adaptive Solutions Implementing Artificial Intelligence -- 5.3 Human-Robot Self-Learning Collaboration in Industrial Applications and Electronic Aspects -- 5.3.1 DC-DC Converter -- 5.3.2 Voltage Source Inverter -- 5.3.3 Current-Source Inverter -- 5.3.4 DC Voltage Source -- 5.3.5 Capacitor and Reactor Effects on Signal Control -- 5.3.6 Human-Robot System and Learning Approaches -- 5.3.6.1 Example of PID Implementation of Self-AdaptingGains -- 5.3.7 Unsupervised Learning Approaches -- 5.3.8 Soft Robotics for Intelligent Collaborative Robotics -- 5.4 Robotics in Additive Manufacturing -- 5.4.1 Additive Manufacturing in Industrial Production and Spray Technique -- 5.4.2 Artificial Intelligence Applications in Additive Manufacturing -- 5.4.3 Advanced Electronic for Design-to-Product Transformation: Laser Texturing Manufacturing and Artificial Intelligence -- References -- Chapter 6 Advanced Optoelectronic and Micro-/Nanosensors -- 6.1 Nanotechnology Laboratories in Industries -- 6.1.1 Facilities for Micro-/Nanosensor Fabrication and Characterization -- 6.2 Micro- and Nanosensors as Preliminary Prototypes for Industry Research -- 6.2.1 Nanocomposite Optoelectronic Sensors and Optoelectronic Circuits for Pressure Sensors -- 6.2.1.1 Optical Fiber Nanocomposite Tip -- 6.2.2 Plasmonic Probes -- 6.2.3 Nanocomposite Pressure Sensor -- 6.2.4 Nanocomposite Sensor for Liquid Detection Systems and Fluid Loss Systems. 6.2.4.1 Nanocomposite Sensor for Liquid Detection Systems Based on a Pillar-Type Layout -- 6.2.4.2 Micro- and Nanosensors in the Monitoring of Production Processes: Leakage Monitoring -- 6.2.5 Examples of Digital MEMS/NEMS Sensors: Technological Aspects and Applications -- 6.2.5.1 Thin Film MEMS -- 6.2.5.2 Nanoprobes for Medical Imaging -- 6.2.5.3 Diamond Thin Film Devices: Sensing Improvements -- 6.3 Multisensor Systems and Big Data Synchronization of Micro-/Nanoprobes -- References -- Chapter 7 Image Vision Advances -- 7.1 Defect Classification by Artificial Intelligence and Data Processor Units -- 7.1.1 Artificial Intelligence Algorithms and Automatism for Defect Classification: Case Study of Tire Production -- 7.1.2 Welding Classification and Nondestructive Testing Suitable for the Quality Check -- 7.1.2.1 Watershed Image Segmentation and Automatic Welding Defect Classification -- 7.1.3 Encoding and Decoding Circuits in Artificial Intelligence Data Processing -- 7.1.4 Electronic Logic Port Implementations: Pixel Matrix Logic Condition -- 7.2 Image Vision Architectures and Electronic Design -- 7.2.1 Infrared Thermography Monitoring Industrial Processes -- 7.2.1.1 Welding Image Vision Processing and Architecture Design: Radiometric Post Processing -- 7.2.2 Electronic and Firmware for Inline Image Monitoring Systems: Hole Precision in Milling Quality Processes -- 7.2.3 Image Vision and Predictive Maintenance by Artificial Intelligence -- 7.2.3.1 Profilometer for Image Vision -- 7.2.3.2 In-Line 3D Image Vision AI System Integrating Profilometer and Image Processing -- 7.2.4 Augmented Reality Systems and Artificial Neural Networks: Image Vision Supporting Production Processes -- 7.2.5 Infrared Thermography Circuit Design and Automated System -- 7.3 Image Segmentation and Image Clustering. 7.3.1 Electronic and Firmware for In-Line Monitoring Systems: Camera Connection. |
| Record Nr. | UNINA-9910555250203321 |
|
Massaro Alessandro <1974->
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Electronics in advanced research industries : industry 4.0 to industry 5.0 advances / / Alessandro Massaro
| Electronics in advanced research industries : industry 4.0 to industry 5.0 advances / / Alessandro Massaro |
| Autore | Massaro Alessandro <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] |
| Descrizione fisica | 1 online resource (538 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
Industry 4.0
Electronics - Safety measures |
| ISBN |
1-119-71689-6
1-119-71690-X 1-119-71688-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- About the Author -- Chapter 1 State of the Art and Technology Innovation -- 1.1 State of the Art of Flexible Technologies in Industry -- 1.1.1 Sensors and Actuators Layer: I/O Layer -- 1.1.2 Agent/Firmware Layer: User Interface Layer -- 1.1.3 Gateway and Enterprise Service Bus Layer -- 1.1.4 IoT Middleware -- 1.1.5 Processing Layer -- 1.1.6 Application Layer -- 1.1.7 File Transfer Protocols -- 1.2 State of the Art of Scientific Approaches Oriented on Process Control and Automatisms -- 1.2.1 Architectures Integrating AI -- 1.2.2 AI Supervised and Unsupersived Algorithms -- 1.2.3 AI Image Processing -- 1.2.4 Production Process Mapping -- 1.2.5 Technologies of Industry 4.0 and Industry 5.0: Interconnection and Main Limits -- 1.2.6 Infrared Thermography in Monitoring Process -- 1.2.7 Key Parameters in Supply Chain and AI Improving Manufacturing Processes -- 1.3 Intelligent Automatic Systems in Industries -- 1.4 Technological Approaches to Transform the Production in Auto-Adaptive Control and Actuation Systems -- 1.5 Basic Concepts of Artificial Intelligence -- 1.6 Knowledge Upgrading in Industries -- References -- Chapter 2 Information Technology Infrastructures Supporting Industry 5.0 Facilities -- 2.1 Production Process Simulation and Object Design Approaches -- 2.1.1 Object Design of a Data Mining Algorithm: Block Functions and Parameter Setting -- 2.1.2 Example 1: BPM Modeling of Wheat Storage Process for Pasta Production -- 2.1.3 Example 2: Block Diagram Design of a Servo Valve Control and Actuation System -- 2.1.4 Example 3: Block Diagram of a Liquid Production System -- 2.1.5 Example 4: UML Design of a Programmable Logic Controller System -- 2.1.6 Example 5: Electronic Logic Timing Diagram -- 2.1.7 Example 6: AR System in Kitchen Production Process.
2.1.8 Example 7: Intelligent Canned Food Production Line -- 2.2 Electronic Logic Design Oriented on Information Infrastructure of Industry 5.0 -- 2.3 Predictive Maintenance: Artificial Intelligence Failure Predictions and Information Infrastructure Layout in the Temperature Monitoring Process -- 2.4 Defect Estimation and Prediction by Artificial Neural Network -- 2.4.1 Other Methodologies to Map and Read Production Failures and Defects -- 2.5 Defect Clustering and Classification: Combined Use of the K-Means Algorithm with Infrared Thermography for Predictive Maintenance -- 2.6 Facilities of a Prototype Network Implementing Advanced Technology: Example of an Advanced Platform Suitable for Industry 5.0 Integrating Predictive Maintenance -- 2.7 Predictive Maintenance Approaches -- 2.7.1 Preventive Maintenance and Predictive Maintenance Operations in the Railway Industry -- 2.8 Examples of Advanced Infrastructures Implementing AI -- 2.9 Examples of Telemedicine Platforms Integrating Advanced Facilities -- 2.9.1 Advanced Telecardiology Platform -- 2.9.2 Advanced Teleoncology Platform -- 2.9.3 Multipurpose E-Health Platform -- References -- Chapter 3 Human-Machine Interfaces -- 3.1 Mechatronic Machine Interface Architectures Integrating Sensor Systems -- 3.1.1 Multiple Mechatronic Boards Managing Different Production Stages -- 3.1.2 Mechatronic Boards Managing Component Processing -- 3.2 Machine-to-Machine Interfaces: New Concepts of Industry 5.0 -- 3.3 Production Line Command and Actuation Interfaces in Upgraded Systems -- 3.3.1 PLC, PAC, Industrial PC, and Improvements -- 3.3.2 SCADA Systems for Centralization of Data Production -- 3.4 McCulloch-Pitts Neurons and Logic Port for Automatic Decision-Making Setting Thresholds -- 3.5 Programmable Logic Controller I/O Ports Interfacing with AI Engine. 3.6 Human-Machine Interface for Data Transfer and AI Data Processing -- 3.7 Example of Interface Configuration of Temperature Control -- 3.8 AI Interfaces Oriented on Cybersecurity Attack Detection -- 3.9 AI Interfaces Oriented on Database Security -- 3.10 Cybersecurity Platform and AI Control Interface -- References -- Chapter 4 Internet of Things Solutions in Industry -- 4.1 Cloud Computing IoT -- 4.1.1 IoT Agent -- 4.1.2 IoT Gateway in Smart Environments -- 4.1.3 Basic Elements of a Smart Industry Environment Controlling Production -- 4.1.4 Augmented Reality Hardware and Cloud Computing Processing -- 4.1.5 Real-Time Control and Actuation -- 4.1.6 Localization Technologies in an Industrial Environment -- 4.1.7 GPU Processing Units -- 4.2 IoT and External Artificial Intelligence Engines -- 4.2.1 Artificial Engines and Server Location: Artificial Intelligence and Adaptive Production -- 4.2.2 IoT Security Systems in the Working Environment and Implementation Aspects -- 4.2.3 Example of Energy Power Control and Actuation: Energy Routing and Priority Load Management for Energy Efficiency -- 4.2.4 Online Configurators: Cloud DSS -- 4.3 Blockchain and IoT Data Storage Systems -- 4.3.1 Blockchain Implementation Rules -- 4.3.2 Blockchain and IoT Production Traceability -- 4.4 Mechatronic Machine Interface Architectures Integrating Sensor Systems -- 4.5 Multiple Mechatronic Boards Managing Different Production Stages -- References -- Chapter 5 Advanced Robotics -- 5.1 Collaborative Robotics in Industry and Protocols -- 5.1.1 Data Protocols -- 5.1.2 Basic Concepts of Robotic Arms and Control Improvement -- 5.1.3 Collaborative Exoskeleton Communication System Protocols -- 5.1.4 Advanced Robotics and Intelligent Automation in Manufacturing: Logic Conditions and PLC Programming -- 5.2 Artificial Intelligence in Advanced Robotics and Auto-Adaptive Movement. 5.2.1 General Technological Aspects about Auto-Adaptive Motion in Advanced Robotics -- 5.2.1.1 Main Aspects of Electrostatic Actuators -- 5.2.1.2 Microelectromechanical System Electrostatic Actuators -- 5.2.1.3 Piezoelectric Actuators -- 5.2.1.4 DC Motor Actuation -- 5.2.1.5 Intelligent Control Integrating AI: Speed Regulation -- 5.2.2 Improvement of Collaborative Exoskeletons by Auto-Adaptive Solutions Implementing Artificial Intelligence -- 5.3 Human-Robot Self-Learning Collaboration in Industrial Applications and Electronic Aspects -- 5.3.1 DC-DC Converter -- 5.3.2 Voltage Source Inverter -- 5.3.3 Current-Source Inverter -- 5.3.4 DC Voltage Source -- 5.3.5 Capacitor and Reactor Effects on Signal Control -- 5.3.6 Human-Robot System and Learning Approaches -- 5.3.6.1 Example of PID Implementation of Self-AdaptingGains -- 5.3.7 Unsupervised Learning Approaches -- 5.3.8 Soft Robotics for Intelligent Collaborative Robotics -- 5.4 Robotics in Additive Manufacturing -- 5.4.1 Additive Manufacturing in Industrial Production and Spray Technique -- 5.4.2 Artificial Intelligence Applications in Additive Manufacturing -- 5.4.3 Advanced Electronic for Design-to-Product Transformation: Laser Texturing Manufacturing and Artificial Intelligence -- References -- Chapter 6 Advanced Optoelectronic and Micro-/Nanosensors -- 6.1 Nanotechnology Laboratories in Industries -- 6.1.1 Facilities for Micro-/Nanosensor Fabrication and Characterization -- 6.2 Micro- and Nanosensors as Preliminary Prototypes for Industry Research -- 6.2.1 Nanocomposite Optoelectronic Sensors and Optoelectronic Circuits for Pressure Sensors -- 6.2.1.1 Optical Fiber Nanocomposite Tip -- 6.2.2 Plasmonic Probes -- 6.2.3 Nanocomposite Pressure Sensor -- 6.2.4 Nanocomposite Sensor for Liquid Detection Systems and Fluid Loss Systems. 6.2.4.1 Nanocomposite Sensor for Liquid Detection Systems Based on a Pillar-Type Layout -- 6.2.4.2 Micro- and Nanosensors in the Monitoring of Production Processes: Leakage Monitoring -- 6.2.5 Examples of Digital MEMS/NEMS Sensors: Technological Aspects and Applications -- 6.2.5.1 Thin Film MEMS -- 6.2.5.2 Nanoprobes for Medical Imaging -- 6.2.5.3 Diamond Thin Film Devices: Sensing Improvements -- 6.3 Multisensor Systems and Big Data Synchronization of Micro-/Nanoprobes -- References -- Chapter 7 Image Vision Advances -- 7.1 Defect Classification by Artificial Intelligence and Data Processor Units -- 7.1.1 Artificial Intelligence Algorithms and Automatism for Defect Classification: Case Study of Tire Production -- 7.1.2 Welding Classification and Nondestructive Testing Suitable for the Quality Check -- 7.1.2.1 Watershed Image Segmentation and Automatic Welding Defect Classification -- 7.1.3 Encoding and Decoding Circuits in Artificial Intelligence Data Processing -- 7.1.4 Electronic Logic Port Implementations: Pixel Matrix Logic Condition -- 7.2 Image Vision Architectures and Electronic Design -- 7.2.1 Infrared Thermography Monitoring Industrial Processes -- 7.2.1.1 Welding Image Vision Processing and Architecture Design: Radiometric Post Processing -- 7.2.2 Electronic and Firmware for Inline Image Monitoring Systems: Hole Precision in Milling Quality Processes -- 7.2.3 Image Vision and Predictive Maintenance by Artificial Intelligence -- 7.2.3.1 Profilometer for Image Vision -- 7.2.3.2 In-Line 3D Image Vision AI System Integrating Profilometer and Image Processing -- 7.2.4 Augmented Reality Systems and Artificial Neural Networks: Image Vision Supporting Production Processes -- 7.2.5 Infrared Thermography Circuit Design and Automated System -- 7.3 Image Segmentation and Image Clustering. 7.3.1 Electronic and Firmware for In-Line Monitoring Systems: Camera Connection. |
| Record Nr. | UNINA-9910830526203321 |
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Massaro Alessandro <1974->
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| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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