ISBN-13: 9781119865001 / Angielski / Twarda / 2023 / 340 str.
ISBN-13: 9781119865001 / Angielski / Twarda / 2023 / 340 str.
Preface xvii1 Evolution of Internet of Things (IoT): Past, Present and Future for Manufacturing Systems 1Vaishnavi Vadivelu, Moganapriya Chinnasamy, Manivannan Rajendran, Hari Chandrasekaran and Rajasekar Rathanasamy1.1 Introduction 21.2 IoT Revolution 21.3 IoT 41.4 Fundamental Technologies 51.4.1 RFID and NFC 51.4.2 Wsn 61.4.3 Data Storage and Analytics (DSA) 61.5 IoT Architecture 61.6 Cloud Computing (CC) and IoT 71.6.1 Service of cc 81.6.2 Integration of IoT With cc 101.7 Edge Computing (EC) and IoT 101.7.1 EC with IoT Architecture 111.8 Applications of IoT 121.8.1 Smart Mobility 121.8.2 Smart Grid 141.8.3 Smart Home System 141.8.4 Public Safety and Environment Monitoring 151.8.5 Smart Healthcare Systems 151.8.6 Smart Agriculture System 161.9 Industry 4.0 Integrated With IoT Architecture for Incorporation of Designing and Enhanced Production Systems 171.9.1 Five-Stage Process of IoT for Design and Manufacturing System 191.9.2 IoT Architecture for Advanced Manufacturing Technologies 211.9.3 Architecture Development 221.10 Current Issues and Challenges in IoT 241.10.1 Scalability 251.10.2 Issue of Trust 251.10.3 Service Availability 261.10.4 Security Challenges 261.10.5 Mobility Issues 271.10.6 Architecture for IoT 271.11 Conclusion 28References 292 Fourth Industrial Revolution: Industry 4.0 41Maheswari Rajamanickam, Elizabeth Nirmala John Gerard Royan, Gowtham Ramaswamy, Manivannan Rajendran and Vaishnavi Vadivelu2.1 Introduction 422.1.1 Global Level Adaption 422.2 Evolution of Industry 442.2.1 Industry 1.0 442.2.2 Industry 2.0 442.2.3 Industry 3.0 442.2.4 Industry 4.0 (or) I4. 0 442.3 Basic IoT Concepts and the Term Glossary 452.4 Industrial Revolution 472.4.1 I4.0 Core Idea 472.4.2 Origin of I4.0 Concept 482.5 Industry 492.5.1 Manufacturing Phases 492.5.2 Existing Process Planning vs. I4. 0 502.5.3 Software for Product Planning--A Link Between Smart Products and the Main System ERP 522.6 Industry Production System 4.0 (Smart Factory) 562.6.1 IT Support 582.7 I4.0 in Functional Field 602.7.1 I4.0 Logistics 602.7.2 Resource Planning 602.7.3 Systems for Warehouse Management 612.7.4 Transportation Management Systems 612.7.5 Transportation Systems with Intelligence 632.7.6 Information Security 642.8 Existing Technology in I4. 0 652.8.1 Applications of I4.0 in Existing Industries 652.8.2 Additive Manufacturing (AM) 662.8.3 Intelligent Machines 662.8.4 Robots that are Self-Aware 662.8.5 Materials that are Smart 672.8.6 IoT 672.8.7 The Internet of Things in Industry (IIoT) 672.8.8 Sensors that are Smart 672.8.9 System Using a Smart Programmable Logic Controller (PLC) 672.8.10 Software 682.8.11 Augmented Reality (AR)/Virtual Reality (VR) 682.8.12 Gateway for the Internet of Things 682.8.13 Cloud 682.8.14 Applications of Additive Manufacturing in I4. 0 682.8.15 Artificial Intelligence (AI) 692.9 Applications in Current Industries 692.9.1 I4.0 in Logistics 692.9.2 I4.0 in Manufacturing Operation 702.10 Future Scope of Research 732.10.1 Theoretical Framework of I4. 0 732.11 Discussion and Implications 752.11.1 Hosting: Microsoft 752.11.2 Platform for the Internet of Things (IoT): Microsoft, GE, PTC, and Siemens 762.11.3 A Systematic Computational Analysis 762.11.4 Festo Proximity Sensor 772.11.5 Connectivity Hardware: HMS 772.11.6 IT Security: Claroty 772.11.7 Accenture Is a Systems Integrator 772.11.8 Additive Manufacturing: General Electric 782.11.9 Augmented and Virtual Reality: Upskill 782.11.10 ABB Collaborative Robots 782.11.11 Connected Vision System: Cognex 782.11.12 Drones/UAVs: PINC 792.11.13 Self-Driving in Vehicles: Clear Path Robotics 792.12 Conclusion 79References 803 Interaction of Internet of Things and Sensors for Machining 85Manivannan Rajendran, Kamesh Nagarajan, Vaishnavi Vadivelu, Harikrishna Kumar Mohankumar and Sathish Kumar Palaniappan3.1 Introduction 863.2 Various Sensors Involved in Machining Process 883.2.1 Direct Method Sensors 893.2.2 Indirect Method Sensors 893.2.3 Dynamometer 903.2.4 Accelerometer 913.2.5 Acoustic Emission Sensor 933.2.6 Current Sensors 943.3 Other Sensors 943.3.1 Temperature Sensors 943.3.2 Optical Sensors 953.4 Interaction of Sensors During Machining Operation 963.4.1 Milling Machining 963.4.2 Turning Machining 973.4.3 Drilling Machining Operation 983.5 Sensor Fusion Technique 993.6 Interaction of Internet of Things 1003.6.1 Identification 1003.6.2 Sensing 1013.6.3 Communication 1013.6.4 Computation 1013.6.5 Services 1013.6.6 Semantics 1013.7 IoT Technologies in Manufacturing Process 1023.7.1 IoT Challenges 1023.7.2 IoT-Based Energy Monitoring System 1023.8 Industrial Application 1043.8.1 Integrated Structure 1043.8.2 Monitoring the System Related to Service Based on Internet of Things 1063.9 Decision Making Methods 1073.9.1 Artificial Neural Network 1073.9.2 Fuzzy Inference System 1083.9.3 Support Vector Mechanism 1083.9.4 Decision Trees and Random Forest 1093.9.5 Convolutional Neural Network 1093.10 Conclusion 111References 1114 Application of Internet of Things (IoT) in the Automotive Industry 115Solomon Jenoris Muthiya, Shridhar Anaimuthu, Joshuva Arockia Dhanraj, Nandakumar Selvaraju, Gutha Manikanta and C. Dineshkumar4.1 Introduction 1164.2 Need For IoT in Automobile Field 1184.3 Fault Diagnosis in Automobile 1194.4 Automobile Security and Surveillance System in IoT-Based 1234.5 A Vehicle Communications 1254.6 The Smart Vehicle 1264.7 Connected Vehicles 1284.7.1 Vehicle-to-Vehicle (V2V) Communications 1304.7.2 Vehicle-to-Infrastructure (V2I) Communications 1314.7.3 Vehicle-to-Pedestrian (V2P) Communications 1324.7.4 Vehicle to Network (V2N) Communication 1334.7.5 Vehicle to Cloud (V2C) Communication 1344.7.6 Vehicle to Device (V2D) Communication 1344.7.7 Vehicle to Grid (V2G) Communications 1354.8 Conclusion 135References 1365 IoT for Food and Beverage Manufacturing 141Manju Sri Anbupalani, Gobinath Velu Kaliyannan and Santhosh Sivaraj5.1 Introduction 1425.2 The Influence of IoT in a Food Industry 1435.2.1 Management 1435.2.2 Workers 1435.2.3 Data 1435.2.4 It 1435.3 A Brief Review of IoT's Involvement in the Food Industry 1445.4 Challenges to the Food Industry and Role of IoT 1445.4.1 Handling and Sorting Complex Data 1445.4.2 A Retiring Skilled Workforce 1455.4.3 Alternatives for Supply Chain Management 1455.4.4 Implementation of IoT in Food and Beverage Manufacturing 1455.4.5 Pilot 1455.4.6 Plan 1465.4.7 Proliferate 1465.5 Applications of IoT in a Food Industry 1465.5.1 IoT for Handling of Raw Material and Inventory Control 1465.5.2 Factory Operations and Machine Conditions Using IoT 1465.5.3 Quality Control With the IoT 1475.5.4 IoT for Safety 1475.5.5 The Internet of Things and Sustainability 1475.5.6 IoT for Product Delivery and Packaging 1475.5.7 IoT for Vehicle Optimization 1475.5.8 IoT-Based Water Monitoring Architecture in the Food and Beverage Industry 1485.6 A FW Tracking System Methodology Based on IoT 1505.7 Designing an IoT-Based Digital FW Monitoring and Tracking System 1505.8 The Internet of Things (IoT) Architecture for a Digitized Food Waste System 1525.9 Hardware Design: Intelligent Scale 1525.10 Software Design 153References 1576 Opportunities: Machine Learning for Industrial IoT Applications 159Poongodi C., Sayeekumar M., Meenakshi C. and Hari Prasath K.6.1 Introduction 1606.2 I-IoT Applications 1636.3 Machine Learning Algorithms for Industrial IoT 1706.3.1 Supervised Learning 1716.3.2 Semisupervised Learning 1736.3.3 Unsupervised Learning 1736.3.4 Reinforcement Learning 1756.3.5 The Most Common and Popular Machine Learning Algorithms 1766.4 I-IoT Data Analytics 1776.4.1 Tools for IoT Analytics 1776.4.2 Choosing the Right IoT Data Analytics Platforms 1846.5 Conclusion 185References 1867 Role of IoT in Industry Predictive Maintenance 191Gobinath Velu Kaliyannan, Manju Sri Anbupalani, Suganeswaran Kandasamy, Santhosh Sivaraj and Raja Gunasekaran7.1 Introduction 1927.2 Predictive Maintenance 1947.3 IPdM Systems Framework and Few Key Methodologies 1967.3.1 Detection and Collection of Data 1967.3.2 Initial Processing of Collected Data 1967.3.3 Modeling as Per Requirement 1977.3.4 Influential Parameters 1987.3.5 Identification of Best Working Path 1987.3.6 Modifying Output with Respect Sensed Input 1987.4 Economics of PdM 1987.5 PdM for Production and Product 2007.6 Implementation of IPdM 2027.6.1 Manufacturing with Zero Defects 2027.6.2 Sense of the Windsene INDSENSE 2027.7 Case Studies 2027.7.1 Area 1--Heavy Ash Evacuation 2037.7.2 Area 2--Seawater Pumps 2037.7.3 Evaporators 2047.7.4 System Deployment Considerations in General 2057.8 Automotive Industry--Integrated IoT 2057.8.1 Navigation Aspect 2057.8.2 Continual Working of Toll Booth 2067.8.3 Theft Security System 2067.8.4 Black Box-Enabled IoT 2067.8.5 Regularizing Motion of Emergency Vehicle 2077.8.6 Pollution Monitoring System 2077.8.7 Timely Assessment of Driver's Condition 2077.8.8 Vehicle Performance Monitoring 2077.9 Conclusion 208References 2088 Role of IoT in Product Development 215Bhuvanesh Kumar M., Balaji N. S., Senthil S. M. and Sathiya P.8.1 Introduction 2168.1.1 Industry 4.0 2178.2 Need to Understand the Product Architecture 2208.3 Product Development Process 2228.3.1 Criteria to Classify the New Products 2238.3.2 Product Configuration 2248.3.3 Challenges in Product Development while Developing IoT Products (Data-Driven Product Development) 2258.3.4 Role of IoT in Product Development for Industrial Applications 2268.3.5 Impacts and Future Perspectives of IoT in Product Development 2298.4 Conclusion 231References 2329 Benefits of IoT in Automated Systems 235Adithya K. and Girimurugan R.9.1 Introduction 2359.2 Benefits of Automation 2369.2.1 Improved Productivity 2369.2.2 Efficient Operation Management 2369.2.3 Better Use of Resources 2379.2.4 Cost-Effective Operation 2379.2.5 Improved Work Safety 2379.2.6 Software Bots 2379.2.7 Enhanced Public Sector Operations 2379.2.8 Healthcare Benefits 2389.3 Smart City Automation 2389.3.1 Smart Agriculture 2409.3.2 Smart City Services 2409.3.3 Smart Energy 2409.3.4 Smart Health 2419.3.5 Smart Home 2419.3.6 Smart Industry 2429.3.7 Smart Infrastructure 2429.3.8 Smart Transport 2429.4 Smart Home Automation 2439.5 Automation in Manufacturing 2479.5.1 IoT Manufacturing Use Cases 2499.5.2 Foundation for IoT in Manufacturing 2519.6 Healthcare Automation 2539.6.1 IoT in Healthcare Applications 2549.6.2 Architecture for IoT-Healthcare Applications 2579.6.3 Challenges and Solutions 2589.7 Industrial Automation 2599.7.1 IoT in Industrial Automation 2609.7.2 The Essentials of an Industrial IoT Solution 2609.7.3 Practical Industrial IoT Examples for Daily Use 2619.8 Automation in Air Pollution Monitoring 2659.8.1 Methodology 2669.8.2 Working Principle 2679.8.3 Results 2679.9 Irrigation Automation 268References 26910 Integration of IoT in Energy Management 271Ganesh Angappan, Santhosh Sivaraj, Premkumar Bhuvaneshwaran, Mugilan Thanigachalam, Sarath Sekar and Rajasekar Rathanasamy10.1 Introduction 27210.2 Energy Management Integration with IoT in Industry 4.0 27410.3 IoT in Energy Sector 27610.3.1 Energy Generation 27610.3.2 Smart Cities 27710.3.3 Smart Grid 27710.3.4 Smart Buildings 27810.3.5 IoT in the Energy Industry 27910.3.6 Intelligent Transportation 28010.4 Provocations in the IoT Applications 28110.4.1 Energy Consumption 28110.4.2 Subsystems and IoT Integration 28210.5 Energy Generation 28410.5.1 Conversion of Mechanical Energy 28510.5.2 Aeroelastic Energy Harvesting 29010.5.3 Solar Energy Harvesting 29210.5.4 Sound Energy Harvesting 29210.5.5 Wind Energy Harvesting 29210.5.6 Radiofrequency Energy Harvesting 29310.5.7 Thermal Energy 29310.6 Conclusion 294References 29411 Role of IoT in the Renewable Energy Sector 305Veerakumar Chinnasamy and Honghyun Cho11.1 Introduction 30511.2 Internet of Things (IoT) 30611.3 IoT in the Renewable Energy Sector 30711.3.1 Automation of Energy Generation 30711.3.2 Smart Grids 30911.3.3 IoT Increases the Renewable Energy Use 31211.3.4 Consumer Contribution 31211.3.5 Balancing Supply and Demand 31311.3.6 Smart Buildings 31311.3.7 Smart Cities 31411.3.8 Cost-Effectiveness 31411.4 Data Analytics 31411.4.1 Data Forecasting 31411.4.2 Safety and Reliability 31511.5 Conclusion 315References 315Index 317
R. Rajasekar, PhD, Professor and Head of the Department of Mechanical Engineering, Kongu Engineering College (An Autonomous Institution under Anna University), Tamilnadu, India. He obtained his PhD from the Indian Institute of Technology, Kharagpur, and specializes in materials science and engineering, renewable energy, surface coating on solar cells, and tribological performance of carbide inserts. He has published more than 100 research articles in reputed international journals as well as more than 30 book chapters.C. Moganapriya, PhD, is an associate professor in the Department of Mechanical Engineering, Kongu Engineering College (An Autonomous Institution under Anna University), Tamilnadu, India. She completed her PhD in 2019 and her current research area includes surface engineering of solar cells for performance enhancement of power conversion efficiency and tribological performance of cutting tool inserts by adopting several hard coating materials. She has published 13 research articles and 15 book chapters with international publishers.P. Sathish Kumar, PhD, is an assistant professor in the Department of Manufacturing, Institute of Mechanical Engineering, Saveetha School of Engineering, SIMATS University, Chennai, Tamilnadu, India. He has published more than 60 research articles and 35 book chapters with international journals and publishers. His main research areas are in tribological studies of mining bits, thin film coating, natural fiber composites and renewable energy.M. Harikrishna Kumar, PhD, is a lecturer at Sri Krishna Polytechnic College, Coimbatore, India. He has 12 years of teaching and 2 years of industry experience. He served as an assistant professor at Kongu Engineering College, Perundurai, India for 9 years.
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