Md Rashid Mahmood, PhD, is a professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. He has published 50 research papers in international/national journals as well as 10 patents. Rohit Raja, PhD, is an associate professor & Head, IT Department, Guru Ghasidas, Vishwavidyalaya, Bilaspur, (CG), India. He has published 80 research papers in international/national journals as well as 13 patents. Harpreet Kaur, PhD, is an associate professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. Her research interests include vehicle detection and tracking in autonomous vehicles, and image processing. Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published 85 research papers in international/national journals as well as 9 patents. Kapil Kumar Nagwanshi, PhD, is an associate professor at SoS E&T, Guru Ghasidas Vishwavidyalaya, Bilaspur, India. He has published more the 25 articles in SCI and Scopus-indexed Journals, and six patents were granted. His area of interest includes AI-ML, computer vision, and IoT.

• Preface xv1 Ambient Intelligence and Internet of Things: An Overview 1Md Rashid Mahmood, Harpreet Kaur, Manpreet Kaur, Rohit Raja and Imran Ahmed Khan1.1 Introduction 21.2 Ambient Intelligent System 51.3 Characteristics of AmI Systems 61.4 Driving Force for Ambient Computing 91.5 Ambient Intelligence Contributing Technologies 91.6 Architecture Overview 111.7 The Internet of Things 141.8 IoT as the New Revolution 141.9 IoT Challenges 161.10 Role of Artificial Intelligence in the Internet of Things (IoT) 181.11 IoT in Various Domains 191.12 Healthcare 201.13 Home Automation 201.14 Smart City 211.15 Security 211.16 Industry 221.17 Education 231.18 Agriculture 241.19 Tourism 261.20 Environment Monitoring 271.21 Manufacturing and Retail 281.22 Logistics 281.23 Conclusion 29References 292 An Overview of Internet of Things Related Protocols, Technologies, Challenges and Application 33Deevesh Chaudhary and Prakash Chandra Sharma2.1 Introduction 342.1.1 History of IoT 352.1.2 Definition of IoT 362.1.3 Characteristics of IoT 362.2 Messaging Protocols 372.2.1 Constrained Application Protocol 382.2.2 Message Queue Telemetry Transport 392.2.3 Extensible Messaging and Presence Protocol 412.2.4 Advance Message Queuing Protocol (AMQP) 412.3 Enabling Technologies 412.3.1 Wireless Sensor Network 412.3.2 Cloud Computing 422.3.3 Big Data Analytics 432.3.4 Embedded System 432.4 IoT Architecture 442.5 Applications Area 462.6 Challenges and Security Issues 492.7 Conclusion 50References 513 Ambient Intelligence Health Services Using IoT 53Pawan Whig, Ketan Gupta, Nasmin Jiwani and Arun Velu3.1 Introduction 543.2 Background of AML 553.2.1 What is AML? 553.3 AmI Future 583.4 Applications of Ambient Intelligence 603.4.1 Transforming Hospitals and Enhancing Patient Care With the Help of Ambient Intelligence 603.4.2 With Technology, Life After the COVID-19 Pandemic 613.5 Covid-19 633.5.1 Prevention 643.5.2 Symptoms 643.6 Coronavirus Worldwide 653.7 Proposed Framework for COVID- 19 673.8 Hardware and Software 693.8.1 Hardware 693.8.2 Heartbeat Sensor 703.8.3 Principle 703.8.4 Working 703.8.5 Temperature Sensor 713.8.6 Principle 713.8.7 Working 713.8.8 BP Sensor 723.8.9 Principle 723.8.10 Working 723.9 Mini Breadboard 733.10 Node MCU 733.11 Advantages 763.12 Conclusion 76References 764 Security in Ambient Intelligence and Internet of Things 81Salman Arafath Mohammed and Md Rashid Mahmood4.1 Introduction 824.2 Research Areas 844.3 Security Threats and Requirements 844.3.1 Ad Hoc Network Security Threats and Requirements 854.3.1.1 Availability 864.3.1.2 Confidentiality 864.3.1.3 Integrity 864.3.1.4 Key Management and Authorization 864.3.2 Security Threats and Requirements Due to Sensing Capability in the Network 874.3.2.1 Availability 874.3.2.2 Confidentiality 874.3.2.3 Integrity 874.3.2.4 Key Distribution and Management 874.3.2.5 Resilience to Node Capture 884.3.3 Security Threats and Requirements in AmI and IoT Based on Sensor Network 884.3.3.1 Availability 884.3.3.2 Confidentiality 894.3.3.3 Confidentiality of Location 894.3.3.4 Integrity 894.3.3.5 Nonrepudiation 904.3.3.6 Fabrication 904.3.3.7 Intrusion Detection 904.3.3.8 Confidentiality 914.3.3.9 Trust Management 924.4 Security Threats in Existing Routing Protocols that are Designed With No Focus on Security in AmI and IoT Based on Sensor Networks 924.4.1 Infrastructureless 944.4.1.1 Dissemination-Based Routing 944.4.1.2 Context-Based Routing 984.4.2 Infrastructure-Based 994.4.2.1 Network with Fixed Infrastructure 1004.4.2.2 New Routing Strategy for Wireless Sensor Networks to Ensure Source Location Privacy 1004.5 Protocols Designed for Security Keeping Focus on Security at Design Time for AmI and IoT Based on Sensor Network 1014.5.1 Secure Routing Algorithms 1014.5.1.1 Identity-Based Encryption (I.B.E.) Scheme 1014.5.1.2 Policy-Based Cryptography and Public Encryption with Keyword Search 1024.5.1.3 Secure Content-Based Routing 1024.5.1.4 Secure Content-Based Routing Using Local Key Management Scheme 1034.5.1.5 Trust Framework Using Mobile Traces 1034.5.1.6 Policy-Based Authority Evaluation Scheme 1034.5.1.7 Optimized Millionaire’s Problem 1044.5.1.8 Security in Military Operations 1044.5.1.9 A Security Framework Application Based on Wireless Sensor Networks 1044.5.1.10 Trust Evaluation Using Multifactor Method 1054.5.1.11 Prevention of Spoofing Attacks 1054.5.1.12 QoS Routing Protocol 1064.5.1.13 Network Security Virtualization 1064.5.2 Comparison of Routing Algorithms and Impact on Security 1064.5.3 Inducing Intelligence in IoT Networks Using Artificial Intelligence 1114.5.3.1 Fuzzy Logic- 1 1114.5.3.2 Fuzzy Logic- 2 1124.6 Introducing Hybrid Model in Military Application for Enhanced Security 1134.6.1 Overall System Architecture 1144.6.2 Best Candidate Selection 1144.6.3 Simulation Results in Omnet++ 1154.6 Conclusion 117References 1185 Futuristic AI Convergence of Megatrends: IoT and Cloud Computing 125Chanki Pandey, Yogesh Kumar Sahu, Nithiyananthan Kannan, Md Rashid Mahmood, Prabira Kumar Sethy and Santi Kumari Behera5.1 Introduction 1265.1.1 Our Contribution 1285.2 Methodology 1295.2.1 Statistical Information 1305.3 Artificial Intelligence of Things 1315.3.1 Application Areas of IoT Technologies 1325.3.1.1 Energy Management 1325.3.1.2 5G/Wireless Systems 1345.3.1.3 Risk Assessment 1365.3.1.4 Smart City 1385.3.1.5 Health Sectors 1395.4 AI Transforming Cloud Computing 1405.4.1 Application Areas of Cloud Computing 1525.4.2 Energy/Resource Management 1545.4.3 Edge Computing 1555.4.4 Distributed Edge Computing and Edge-of-Things (EoT) 1585.4.5 Fog Computing in Cloud Computing 1585.4.6 Soft Computing and Others 1615.5 Conclusion 174References 1746 Analysis of Internet of Things Acceptance Dimensions in Hospitals 189Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka and Sharad Chandra Srivastava6.1 Introduction 1906.2 Literature Review 1916.2.1 Overview of Internet of Things 1916.2.2 Internet of Things in Healthcare 1916.2.3 Research Hypothesis 1936.2.3.1 Technological Context (TC) 1936.2.3.2 Organizational Context (OC) 1946.2.3.3 Environmental Concerns (EC) 1956.3 Research Methodology 1956.3.1 Demographics of the Respondents 1966.4 Data Analysis 1966.4.1 Reliability and Validity 1966.4.1.1 Cronbach’s Alpha 1966.4.1.2 Composite Reliability 2016.4.2 Exploratory Factor Analysis (EFA) 2016.4.3 Confirmatory Factor Analysis Results 2016.4.3.1 Divergent or Discriminant Validity 2046.4.4 Structural Equation Modeling 2056.5 Discussion 2066.5.1 Technological Context 2066.5.2 Organizational Context 2076.5.3 Environmental Context 2086.6 Conclusion 209References 2097 Role of IoT in Sustainable Healthcare Systems 215Amrita Rai, Ritesh Pratap Singh and Neha Jain7.1 Introduction 2167.2 Basic Structure of IoT Implementation in the Healthcare Field 2177.3 Different Technologies of IoT for the Healthcare Systems 2217.3.1 On the Basis of the Node Identification 2237.3.2 On the Basis of the Communication Method 2237.3.3 Depending on the Location of the Object 2247.4 Applications and Examples of IoT in the Healthcare Systems 2257.4.1 IoT-Based Healthcare System to Encounter COVID-19 Pandemic Situations 2257.4.2 Wearable Devices 2267.4.3 IoT-Enabled Patient Monitoring Devices From Remote Locations 2277.4.3.1 Pulse Rate Sensor 2277.4.3.2 Respiratory Rate Sensors 2297.4.3.3 Body Temperature Sensors 2317.4.3.4 Blood Pressure Sensing 2327.4.3.5 Pulse Oximetry Sensors 2337.5 Companies Associated With IoT and Healthcare Sector Worldwide 2347.6 Conclusion and Future Enhancement in the Healthcare System With IoT 237References 2388 Fog Computing Paradigm for Internet of Things Applications 243Upendra Verma and Diwakar Bhardwaj8.1 Introduction 2438.2 Challenges 2478.3 Fog Computing: The Emerging Era of Computing Paradigm 2488.3.1 Definition of Fog Computing 2488.3.2 Fog Computing Characteristic 2498.3.3 Comparison Between Cloud and Fog Computing Paradigm 2508.3.4 When to Use Fog Computing 2508.3.5 Fog Computing Architecture for Internet of Things 2518.3.6 Fog Assistance to Address the New IoT Challenges 2528.3.7 Devices Play a Role of Fog Computing Node 2538.4 Related Work 2548.5 Fog Computing Challenges 2548.6 Fog Supported IoT Applications 2628.7 Summary and Conclusion 265References 2659 Application of Internet of Things in Marketing Management 273Arshi Naim, Anandhavalli Muniasamy and Hamed Alqahtani9.1 Introduction 2739.2 Literature Review 2759.2.1 Customer Relationship Management 2769.2.2 Product Life Cycle (PLC) 2779.2.3 Business Process Management (BPM) 2789.2.4 Ambient Intelligence (AmI) 2799.2.5 IoT and CRM Integration 2809.2.6 IoT and BPM Integration 2809.2.7 IoT and Product Life Cycle 2829.2.8 IoT in MMgnt 2829.2.9 Impacts of AmI on Marketing Paradigms 2839.3 Research Methodology 2849.4 Discussion 2849.4.1 Research Proposition 1 2889.4.2 Research Proposition 2 2909.4.3 Research Proposition 3 2919.4.4 Research Proposition 4 2949.4.5 Research Proposition 5 2949.5 Results 2959.4 Conclusions 296References 29710 Healthcare Internet of Things: A New Revolution 301Manpreet Kaur, M. Sugadev, Harpreet Kaur, Md Rashid Mahmood and Vikas Maheshwari10.1 Introduction 30210.2 Healthcare IoT Architecture (IoT) 30310.3 Healthcare IoT Technologies 30410.3.1 Technology for Identification 30510.3.2 Location Technology 30610.3.2.1 Mobile-Based IoT 30610.3.2.2 Wearable Devices 30810.3.2.3 Ambient-Assisted Living (AAL) 31410.3.3 Communicative Systems 31510.3.3.1 Radiofrequency Identification 31610.3.3.2 Bluetooth 31610.3.3.3 Zigbee 31710.3.3.4 Near Field Communication 31710.3.3.5 Wireless Fidelity (Wi-Fi) 31810.3.3.6 Satellite Communication 31810.4 Community-Based Healthcare Services 31910.5 Cognitive Computation 32110.6 Adverse Drug Reaction 32310.7 Blockchain 32510.8 Child Health Information 32710.9 Growth in Healthcare IoT 32810.10 Benefits of IoT in Healthcare 32810.11 Conclusion 329References 33011 Detection-Based Visual Object Tracking Based on Enhanced YOLO-Lite and LSTM 339Aayushi Gautam and Sukhwinder Singh11.1 Introduction 34011.2 Related Work 34111.3 Proposed Approach 34311.3.1 Enhanced YOLO-Lite 34411.3.2 Long Short-Term Memory 34611.3.3 Working of Proposed Framework 34711.4 Evaluation Metrics 34911.5 Experimental Results and Discussion 35011.5.1 Implementation Details 35011.5.2 Performance on OTB-2015 35011.5.3 Performance on VOT-2016 35311.5.4 Performance on UAV-123 35411.6 Conclusion 356References 35612 Introduction to AmI and IoT 361Dolly Thankachan12.1 Introduction 36212.1.1 AmI and IoT Characteristics and Definition of Overlaps 36212.1.1.1 Perceptions of “AmI” and the “IoT” 36312.1.2 Prospects and Perils of AmI and the IoT 36412.1.2.1 Assistances and Claim Areas 36412.1.2.2 Intimidations and Contests Relating to AmI and the IoT 36512.2 AmI and the IoT and Environmental and Societal Sustainability: Dangers, Challenges, and Underpinnings 36612.3 Role of AmI and the IoT as New I.C.T.s to Conservational and Social Sustainability 36712.3.1 AmI and the IoT for Environmental Sustainability: Issues, Discernment, and Favoritisms in Tactical Innovation Pursuits 36812.4 The Environmental Influences of AmI and the IoT Technology 36912.4.1 Fundamental Properties 37012.4.2 Boom Properties 37012.4.3 Oblique Outcomes 37112.4.4 Straight Outcome 37212.5 Conclusion 374References 37913 Design of Optimum Construction Site Management Architecture: A Quality Perspective Using Machine Learning Approach 383Kundan Meshram13.1 Introduction 38413.2 Literature Review 38613.3 Proposed Construction Management Model Based on Machine Learning 39013.4 Comparative Analysis 39313.5 Conclusion 395References 396Index 399

Md Rashid Mahmood, PhD, is a professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. He has published 50 research papers in international/national journals as well as 10 patents. Rohit Raja, PhD, is an associate professor & Head, IT Department, Guru Ghasidas, Vishwavidyalaya, Bilaspur, (CG), India. He has published 80 research papers in international/national journals as well as 13 patents. Harpreet Kaur, PhD, is an associate professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. Her research interests include vehicle detection and tracking in autonomous vehicles, and image processing. Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published 85 research papers in international/national journals as well as 9 patents. Kapil Kumar Nagwanshi, PhD, is an associate professor at SoS E&T, Guru Ghasidas Vishwavidyalaya, Bilaspur, India. He has published more the 25 articles in SCI and Scopus-indexed Journals, and six patents were granted. His area of interest includes AI-ML, computer vision, and IoT.

• Preface xv1 Ambient Intelligence and Internet of Things: An Overview 1Md Rashid Mahmood, Harpreet Kaur, Manpreet Kaur, Rohit Raja and Imran Ahmed Khan1.1 Introduction 21.2 Ambient Intelligent System 51.3 Characteristics of AmI Systems 61.4 Driving Force for Ambient Computing 91.5 Ambient Intelligence Contributing Technologies 91.6 Architecture Overview 111.7 The Internet of Things 141.8 IoT as the New Revolution 141.9 IoT Challenges 161.10 Role of Artificial Intelligence in the Internet of Things (IoT) 181.11 IoT in Various Domains 191.12 Healthcare 201.13 Home Automation 201.14 Smart City 211.15 Security 211.16 Industry 221.17 Education 231.18 Agriculture 241.19 Tourism 261.20 Environment Monitoring 271.21 Manufacturing and Retail 281.22 Logistics 281.23 Conclusion 29References 292 An Overview of Internet of Things Related Protocols, Technologies, Challenges and Application 33Deevesh Chaudhary and Prakash Chandra Sharma2.1 Introduction 342.1.1 History of IoT 352.1.2 Definition of IoT 362.1.3 Characteristics of IoT 362.2 Messaging Protocols 372.2.1 Constrained Application Protocol 382.2.2 Message Queue Telemetry Transport 392.2.3 Extensible Messaging and Presence Protocol 412.2.4 Advance Message Queuing Protocol (AMQP) 412.3 Enabling Technologies 412.3.1 Wireless Sensor Network 412.3.2 Cloud Computing 422.3.3 Big Data Analytics 432.3.4 Embedded System 432.4 IoT Architecture 442.5 Applications Area 462.6 Challenges and Security Issues 492.7 Conclusion 50References 513 Ambient Intelligence Health Services Using IoT 53Pawan Whig, Ketan Gupta, Nasmin Jiwani and Arun Velu3.1 Introduction 543.2 Background of AML 553.2.1 What is AML? 553.3 AmI Future 583.4 Applications of Ambient Intelligence 603.4.1 Transforming Hospitals and Enhancing Patient Care With the Help of Ambient Intelligence 603.4.2 With Technology, Life After the COVID-19 Pandemic 613.5 Covid-19 633.5.1 Prevention 643.5.2 Symptoms 643.6 Coronavirus Worldwide 653.7 Proposed Framework for COVID- 19 673.8 Hardware and Software 693.8.1 Hardware 693.8.2 Heartbeat Sensor 703.8.3 Principle 703.8.4 Working 703.8.5 Temperature Sensor 713.8.6 Principle 713.8.7 Working 713.8.8 BP Sensor 723.8.9 Principle 723.8.10 Working 723.9 Mini Breadboard 733.10 Node MCU 733.11 Advantages 763.12 Conclusion 76References 764 Security in Ambient Intelligence and Internet of Things 81Salman Arafath Mohammed and Md Rashid Mahmood4.1 Introduction 824.2 Research Areas 844.3 Security Threats and Requirements 844.3.1 Ad Hoc Network Security Threats and Requirements 854.3.1.1 Availability 864.3.1.2 Confidentiality 864.3.1.3 Integrity 864.3.1.4 Key Management and Authorization 864.3.2 Security Threats and Requirements Due to Sensing Capability in the Network 874.3.2.1 Availability 874.3.2.2 Confidentiality 874.3.2.3 Integrity 874.3.2.4 Key Distribution and Management 874.3.2.5 Resilience to Node Capture 884.3.3 Security Threats and Requirements in AmI and IoT Based on Sensor Network 884.3.3.1 Availability 884.3.3.2 Confidentiality 894.3.3.3 Confidentiality of Location 894.3.3.4 Integrity 894.3.3.5 Nonrepudiation 904.3.3.6 Fabrication 904.3.3.7 Intrusion Detection 904.3.3.8 Confidentiality 914.3.3.9 Trust Management 924.4 Security Threats in Existing Routing Protocols that are Designed With No Focus on Security in AmI and IoT Based on Sensor Networks 924.4.1 Infrastructureless 944.4.1.1 Dissemination-Based Routing 944.4.1.2 Context-Based Routing 984.4.2 Infrastructure-Based 994.4.2.1 Network with Fixed Infrastructure 1004.4.2.2 New Routing Strategy for Wireless Sensor Networks to Ensure Source Location Privacy 1004.5 Protocols Designed for Security Keeping Focus on Security at Design Time for AmI and IoT Based on Sensor Network 1014.5.1 Secure Routing Algorithms 1014.5.1.1 Identity-Based Encryption (I.B.E.) Scheme 1014.5.1.2 Policy-Based Cryptography and Public Encryption with Keyword Search 1024.5.1.3 Secure Content-Based Routing 1024.5.1.4 Secure Content-Based Routing Using Local Key Management Scheme 1034.5.1.5 Trust Framework Using Mobile Traces 1034.5.1.6 Policy-Based Authority Evaluation Scheme 1034.5.1.7 Optimized Millionaire’s Problem 1044.5.1.8 Security in Military Operations 1044.5.1.9 A Security Framework Application Based on Wireless Sensor Networks 1044.5.1.10 Trust Evaluation Using Multifactor Method 1054.5.1.11 Prevention of Spoofing Attacks 1054.5.1.12 QoS Routing Protocol 1064.5.1.13 Network Security Virtualization 1064.5.2 Comparison of Routing Algorithms and Impact on Security 1064.5.3 Inducing Intelligence in IoT Networks Using Artificial Intelligence 1114.5.3.1 Fuzzy Logic- 1 1114.5.3.2 Fuzzy Logic- 2 1124.6 Introducing Hybrid Model in Military Application for Enhanced Security 1134.6.1 Overall System Architecture 1144.6.2 Best Candidate Selection 1144.6.3 Simulation Results in Omnet++ 1154.6 Conclusion 117References 1185 Futuristic AI Convergence of Megatrends: IoT and Cloud Computing 125Chanki Pandey, Yogesh Kumar Sahu, Nithiyananthan Kannan, Md Rashid Mahmood, Prabira Kumar Sethy and Santi Kumari Behera5.1 Introduction 1265.1.1 Our Contribution 1285.2 Methodology 1295.2.1 Statistical Information 1305.3 Artificial Intelligence of Things 1315.3.1 Application Areas of IoT Technologies 1325.3.1.1 Energy Management 1325.3.1.2 5G/Wireless Systems 1345.3.1.3 Risk Assessment 1365.3.1.4 Smart City 1385.3.1.5 Health Sectors 1395.4 AI Transforming Cloud Computing 1405.4.1 Application Areas of Cloud Computing 1525.4.2 Energy/Resource Management 1545.4.3 Edge Computing 1555.4.4 Distributed Edge Computing and Edge-of-Things (EoT) 1585.4.5 Fog Computing in Cloud Computing 1585.4.6 Soft Computing and Others 1615.5 Conclusion 174References 1746 Analysis of Internet of Things Acceptance Dimensions in Hospitals 189Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka and Sharad Chandra Srivastava6.1 Introduction 1906.2 Literature Review 1916.2.1 Overview of Internet of Things 1916.2.2 Internet of Things in Healthcare 1916.2.3 Research Hypothesis 1936.2.3.1 Technological Context (TC) 1936.2.3.2 Organizational Context (OC) 1946.2.3.3 Environmental Concerns (EC) 1956.3 Research Methodology 1956.3.1 Demographics of the Respondents 1966.4 Data Analysis 1966.4.1 Reliability and Validity 1966.4.1.1 Cronbach’s Alpha 1966.4.1.2 Composite Reliability 2016.4.2 Exploratory Factor Analysis (EFA) 2016.4.3 Confirmatory Factor Analysis Results 2016.4.3.1 Divergent or Discriminant Validity 2046.4.4 Structural Equation Modeling 2056.5 Discussion 2066.5.1 Technological Context 2066.5.2 Organizational Context 2076.5.3 Environmental Context 2086.6 Conclusion 209References 2097 Role of IoT in Sustainable Healthcare Systems 215Amrita Rai, Ritesh Pratap Singh and Neha Jain7.1 Introduction 2167.2 Basic Structure of IoT Implementation in the Healthcare Field 2177.3 Different Technologies of IoT for the Healthcare Systems 2217.3.1 On the Basis of the Node Identification 2237.3.2 On the Basis of the Communication Method 2237.3.3 Depending on the Location of the Object 2247.4 Applications and Examples of IoT in the Healthcare Systems 2257.4.1 IoT-Based Healthcare System to Encounter COVID-19 Pandemic Situations 2257.4.2 Wearable Devices 2267.4.3 IoT-Enabled Patient Monitoring Devices From Remote Locations 2277.4.3.1 Pulse Rate Sensor 2277.4.3.2 Respiratory Rate Sensors 2297.4.3.3 Body Temperature Sensors 2317.4.3.4 Blood Pressure Sensing 2327.4.3.5 Pulse Oximetry Sensors 2337.5 Companies Associated With IoT and Healthcare Sector Worldwide 2347.6 Conclusion and Future Enhancement in the Healthcare System With IoT 237References 2388 Fog Computing Paradigm for Internet of Things Applications 243Upendra Verma and Diwakar Bhardwaj8.1 Introduction 2438.2 Challenges 2478.3 Fog Computing: The Emerging Era of Computing Paradigm 2488.3.1 Definition of Fog Computing 2488.3.2 Fog Computing Characteristic 2498.3.3 Comparison Between Cloud and Fog Computing Paradigm 2508.3.4 When to Use Fog Computing 2508.3.5 Fog Computing Architecture for Internet of Things 2518.3.6 Fog Assistance to Address the New IoT Challenges 2528.3.7 Devices Play a Role of Fog Computing Node 2538.4 Related Work 2548.5 Fog Computing Challenges 2548.6 Fog Supported IoT Applications 2628.7 Summary and Conclusion 265References 2659 Application of Internet of Things in Marketing Management 273Arshi Naim, Anandhavalli Muniasamy and Hamed Alqahtani9.1 Introduction 2739.2 Literature Review 2759.2.1 Customer Relationship Management 2769.2.2 Product Life Cycle (PLC) 2779.2.3 Business Process Management (BPM) 2789.2.4 Ambient Intelligence (AmI) 2799.2.5 IoT and CRM Integration 2809.2.6 IoT and BPM Integration 2809.2.7 IoT and Product Life Cycle 2829.2.8 IoT in MMgnt 2829.2.9 Impacts of AmI on Marketing Paradigms 2839.3 Research Methodology 2849.4 Discussion 2849.4.1 Research Proposition 1 2889.4.2 Research Proposition 2 2909.4.3 Research Proposition 3 2919.4.4 Research Proposition 4 2949.4.5 Research Proposition 5 2949.5 Results 2959.4 Conclusions 296References 29710 Healthcare Internet of Things: A New Revolution 301Manpreet Kaur, M. Sugadev, Harpreet Kaur, Md Rashid Mahmood and Vikas Maheshwari10.1 Introduction 30210.2 Healthcare IoT Architecture (IoT) 30310.3 Healthcare IoT Technologies 30410.3.1 Technology for Identification 30510.3.2 Location Technology 30610.3.2.1 Mobile-Based IoT 30610.3.2.2 Wearable Devices 30810.3.2.3 Ambient-Assisted Living (AAL) 31410.3.3 Communicative Systems 31510.3.3.1 Radiofrequency Identification 31610.3.3.2 Bluetooth 31610.3.3.3 Zigbee 31710.3.3.4 Near Field Communication 31710.3.3.5 Wireless Fidelity (Wi-Fi) 31810.3.3.6 Satellite Communication 31810.4 Community-Based Healthcare Services 31910.5 Cognitive Computation 32110.6 Adverse Drug Reaction 32310.7 Blockchain 32510.8 Child Health Information 32710.9 Growth in Healthcare IoT 32810.10 Benefits of IoT in Healthcare 32810.11 Conclusion 329References 33011 Detection-Based Visual Object Tracking Based on Enhanced YOLO-Lite and LSTM 339Aayushi Gautam and Sukhwinder Singh11.1 Introduction 34011.2 Related Work 34111.3 Proposed Approach 34311.3.1 Enhanced YOLO-Lite 34411.3.2 Long Short-Term Memory 34611.3.3 Working of Proposed Framework 34711.4 Evaluation Metrics 34911.5 Experimental Results and Discussion 35011.5.1 Implementation Details 35011.5.2 Performance on OTB-2015 35011.5.3 Performance on VOT-2016 35311.5.4 Performance on UAV-123 35411.6 Conclusion 356References 35612 Introduction to AmI and IoT 361Dolly Thankachan12.1 Introduction 36212.1.1 AmI and IoT Characteristics and Definition of Overlaps 36212.1.1.1 Perceptions of “AmI” and the “IoT” 36312.1.2 Prospects and Perils of AmI and the IoT 36412.1.2.1 Assistances and Claim Areas 36412.1.2.2 Intimidations and Contests Relating to AmI and the IoT 36512.2 AmI and the IoT and Environmental and Societal Sustainability: Dangers, Challenges, and Underpinnings 36612.3 Role of AmI and the IoT as New I.C.T.s to Conservational and Social Sustainability 36712.3.1 AmI and the IoT for Environmental Sustainability: Issues, Discernment, and Favoritisms in Tactical Innovation Pursuits 36812.4 The Environmental Influences of AmI and the IoT Technology 36912.4.1 Fundamental Properties 37012.4.2 Boom Properties 37012.4.3 Oblique Outcomes 37112.4.4 Straight Outcome 37212.5 Conclusion 374References 37913 Design of Optimum Construction Site Management Architecture: A Quality Perspective Using Machine Learning Approach 383Kundan Meshram13.1 Introduction 38413.2 Literature Review 38613.3 Proposed Construction Management Model Based on Machine Learning 39013.4 Comparative Analysis 39313.5 Conclusion 395References 396Index 399

Md Rashid Mahmood, PhD, is a professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. He has published 50 research papers in international/national journals as well as 10 patents. Rohit Raja, PhD, is an associate professor & Head, IT Department, Guru Ghasidas, Vishwavidyalaya, Bilaspur, (CG), India. He has published 80 research papers in international/national journals as well as 13 patents. Harpreet Kaur, PhD, is an associate professor in the Department of Electronics and Communication Engineering, Guru Nanak Institutions Technical Campus, Hyderabad, India. Her research interests include vehicle detection and tracking in autonomous vehicles, and image processing. Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published 85 research papers in international/national journals as well as 9 patents. Kapil Kumar Nagwanshi, PhD, is an associate professor at SoS E&T, Guru Ghasidas Vishwavidyalaya, Bilaspur, India. He has published more the 25 articles in SCI and Scopus-indexed Journals, and six patents were granted. His area of interest includes AI-ML, computer vision, and IoT.

• Preface xv1 Ambient Intelligence and Internet of Things: An Overview 1Md Rashid Mahmood, Harpreet Kaur, Manpreet Kaur, Rohit Raja and Imran Ahmed Khan1.1 Introduction 21.2 Ambient Intelligent System 51.3 Characteristics of AmI Systems 61.4 Driving Force for Ambient Computing 91.5 Ambient Intelligence Contributing Technologies 91.6 Architecture Overview 111.7 The Internet of Things 141.8 IoT as the New Revolution 141.9 IoT Challenges 161.10 Role of Artificial Intelligence in the Internet of Things (IoT) 181.11 IoT in Various Domains 191.12 Healthcare 201.13 Home Automation 201.14 Smart City 211.15 Security 211.16 Industry 221.17 Education 231.18 Agriculture 241.19 Tourism 261.20 Environment Monitoring 271.21 Manufacturing and Retail 281.22 Logistics 281.23 Conclusion 29References 292 An Overview of Internet of Things Related Protocols, Technologies, Challenges and Application 33Deevesh Chaudhary and Prakash Chandra Sharma2.1 Introduction 342.1.1 History of IoT 352.1.2 Definition of IoT 362.1.3 Characteristics of IoT 362.2 Messaging Protocols 372.2.1 Constrained Application Protocol 382.2.2 Message Queue Telemetry Transport 392.2.3 Extensible Messaging and Presence Protocol 412.2.4 Advance Message Queuing Protocol (AMQP) 412.3 Enabling Technologies 412.3.1 Wireless Sensor Network 412.3.2 Cloud Computing 422.3.3 Big Data Analytics 432.3.4 Embedded System 432.4 IoT Architecture 442.5 Applications Area 462.6 Challenges and Security Issues 492.7 Conclusion 50References 513 Ambient Intelligence Health Services Using IoT 53Pawan Whig, Ketan Gupta, Nasmin Jiwani and Arun Velu3.1 Introduction 543.2 Background of AML 553.2.1 What is AML? 553.3 AmI Future 583.4 Applications of Ambient Intelligence 603.4.1 Transforming Hospitals and Enhancing Patient Care With the Help of Ambient Intelligence 603.4.2 With Technology, Life After the COVID-19 Pandemic 613.5 Covid-19 633.5.1 Prevention 643.5.2 Symptoms 643.6 Coronavirus Worldwide 653.7 Proposed Framework for COVID- 19 673.8 Hardware and Software 693.8.1 Hardware 693.8.2 Heartbeat Sensor 703.8.3 Principle 703.8.4 Working 703.8.5 Temperature Sensor 713.8.6 Principle 713.8.7 Working 713.8.8 BP Sensor 723.8.9 Principle 723.8.10 Working 723.9 Mini Breadboard 733.10 Node MCU 733.11 Advantages 763.12 Conclusion 76References 764 Security in Ambient Intelligence and Internet of Things 81Salman Arafath Mohammed and Md Rashid Mahmood4.1 Introduction 824.2 Research Areas 844.3 Security Threats and Requirements 844.3.1 Ad Hoc Network Security Threats and Requirements 854.3.1.1 Availability 864.3.1.2 Confidentiality 864.3.1.3 Integrity 864.3.1.4 Key Management and Authorization 864.3.2 Security Threats and Requirements Due to Sensing Capability in the Network 874.3.2.1 Availability 874.3.2.2 Confidentiality 874.3.2.3 Integrity 874.3.2.4 Key Distribution and Management 874.3.2.5 Resilience to Node Capture 884.3.3 Security Threats and Requirements in AmI and IoT Based on Sensor Network 884.3.3.1 Availability 884.3.3.2 Confidentiality 894.3.3.3 Confidentiality of Location 894.3.3.4 Integrity 894.3.3.5 Nonrepudiation 904.3.3.6 Fabrication 904.3.3.7 Intrusion Detection 904.3.3.8 Confidentiality 914.3.3.9 Trust Management 924.4 Security Threats in Existing Routing Protocols that are Designed With No Focus on Security in AmI and IoT Based on Sensor Networks 924.4.1 Infrastructureless 944.4.1.1 Dissemination-Based Routing 944.4.1.2 Context-Based Routing 984.4.2 Infrastructure-Based 994.4.2.1 Network with Fixed Infrastructure 1004.4.2.2 New Routing Strategy for Wireless Sensor Networks to Ensure Source Location Privacy 1004.5 Protocols Designed for Security Keeping Focus on Security at Design Time for AmI and IoT Based on Sensor Network 1014.5.1 Secure Routing Algorithms 1014.5.1.1 Identity-Based Encryption (I.B.E.) Scheme 1014.5.1.2 Policy-Based Cryptography and Public Encryption with Keyword Search 1024.5.1.3 Secure Content-Based Routing 1024.5.1.4 Secure Content-Based Routing Using Local Key Management Scheme 1034.5.1.5 Trust Framework Using Mobile Traces 1034.5.1.6 Policy-Based Authority Evaluation Scheme 1034.5.1.7 Optimized Millionaire’s Problem 1044.5.1.8 Security in Military Operations 1044.5.1.9 A Security Framework Application Based on Wireless Sensor Networks 1044.5.1.10 Trust Evaluation Using Multifactor Method 1054.5.1.11 Prevention of Spoofing Attacks 1054.5.1.12 QoS Routing Protocol 1064.5.1.13 Network Security Virtualization 1064.5.2 Comparison of Routing Algorithms and Impact on Security 1064.5.3 Inducing Intelligence in IoT Networks Using Artificial Intelligence 1114.5.3.1 Fuzzy Logic- 1 1114.5.3.2 Fuzzy Logic- 2 1124.6 Introducing Hybrid Model in Military Application for Enhanced Security 1134.6.1 Overall System Architecture 1144.6.2 Best Candidate Selection 1144.6.3 Simulation Results in Omnet++ 1154.6 Conclusion 117References 1185 Futuristic AI Convergence of Megatrends: IoT and Cloud Computing 125Chanki Pandey, Yogesh Kumar Sahu, Nithiyananthan Kannan, Md Rashid Mahmood, Prabira Kumar Sethy and Santi Kumari Behera5.1 Introduction 1265.1.1 Our Contribution 1285.2 Methodology 1295.2.1 Statistical Information 1305.3 Artificial Intelligence of Things 1315.3.1 Application Areas of IoT Technologies 1325.3.1.1 Energy Management 1325.3.1.2 5G/Wireless Systems 1345.3.1.3 Risk Assessment 1365.3.1.4 Smart City 1385.3.1.5 Health Sectors 1395.4 AI Transforming Cloud Computing 1405.4.1 Application Areas of Cloud Computing 1525.4.2 Energy/Resource Management 1545.4.3 Edge Computing 1555.4.4 Distributed Edge Computing and Edge-of-Things (EoT) 1585.4.5 Fog Computing in Cloud Computing 1585.4.6 Soft Computing and Others 1615.5 Conclusion 174References 1746 Analysis of Internet of Things Acceptance Dimensions in Hospitals 189Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka and Sharad Chandra Srivastava6.1 Introduction 1906.2 Literature Review 1916.2.1 Overview of Internet of Things 1916.2.2 Internet of Things in Healthcare 1916.2.3 Research Hypothesis 1936.2.3.1 Technological Context (TC) 1936.2.3.2 Organizational Context (OC) 1946.2.3.3 Environmental Concerns (EC) 1956.3 Research Methodology 1956.3.1 Demographics of the Respondents 1966.4 Data Analysis 1966.4.1 Reliability and Validity 1966.4.1.1 Cronbach’s Alpha 1966.4.1.2 Composite Reliability 2016.4.2 Exploratory Factor Analysis (EFA) 2016.4.3 Confirmatory Factor Analysis Results 2016.4.3.1 Divergent or Discriminant Validity 2046.4.4 Structural Equation Modeling 2056.5 Discussion 2066.5.1 Technological Context 2066.5.2 Organizational Context 2076.5.3 Environmental Context 2086.6 Conclusion 209References 2097 Role of IoT in Sustainable Healthcare Systems 215Amrita Rai, Ritesh Pratap Singh and Neha Jain7.1 Introduction 2167.2 Basic Structure of IoT Implementation in the Healthcare Field 2177.3 Different Technologies of IoT for the Healthcare Systems 2217.3.1 On the Basis of the Node Identification 2237.3.2 On the Basis of the Communication Method 2237.3.3 Depending on the Location of the Object 2247.4 Applications and Examples of IoT in the Healthcare Systems 2257.4.1 IoT-Based Healthcare System to Encounter COVID-19 Pandemic Situations 2257.4.2 Wearable Devices 2267.4.3 IoT-Enabled Patient Monitoring Devices From Remote Locations 2277.4.3.1 Pulse Rate Sensor 2277.4.3.2 Respiratory Rate Sensors 2297.4.3.3 Body Temperature Sensors 2317.4.3.4 Blood Pressure Sensing 2327.4.3.5 Pulse Oximetry Sensors 2337.5 Companies Associated With IoT and Healthcare Sector Worldwide 2347.6 Conclusion and Future Enhancement in the Healthcare System With IoT 237References 2388 Fog Computing Paradigm for Internet of Things Applications 243Upendra Verma and Diwakar Bhardwaj8.1 Introduction 2438.2 Challenges 2478.3 Fog Computing: The Emerging Era of Computing Paradigm 2488.3.1 Definition of Fog Computing 2488.3.2 Fog Computing Characteristic 2498.3.3 Comparison Between Cloud and Fog Computing Paradigm 2508.3.4 When to Use Fog Computing 2508.3.5 Fog Computing Architecture for Internet of Things 2518.3.6 Fog Assistance to Address the New IoT Challenges 2528.3.7 Devices Play a Role of Fog Computing Node 2538.4 Related Work 2548.5 Fog Computing Challenges 2548.6 Fog Supported IoT Applications 2628.7 Summary and Conclusion 265References 2659 Application of Internet of Things in Marketing Management 273Arshi Naim, Anandhavalli Muniasamy and Hamed Alqahtani9.1 Introduction 2739.2 Literature Review 2759.2.1 Customer Relationship Management 2769.2.2 Product Life Cycle (PLC) 2779.2.3 Business Process Management (BPM) 2789.2.4 Ambient Intelligence (AmI) 2799.2.5 IoT and CRM Integration 2809.2.6 IoT and BPM Integration 2809.2.7 IoT and Product Life Cycle 2829.2.8 IoT in MMgnt 2829.2.9 Impacts of AmI on Marketing Paradigms 2839.3 Research Methodology 2849.4 Discussion 2849.4.1 Research Proposition 1 2889.4.2 Research Proposition 2 2909.4.3 Research Proposition 3 2919.4.4 Research Proposition 4 2949.4.5 Research Proposition 5 2949.5 Results 2959.4 Conclusions 296References 29710 Healthcare Internet of Things: A New Revolution 301Manpreet Kaur, M. Sugadev, Harpreet Kaur, Md Rashid Mahmood and Vikas Maheshwari10.1 Introduction 30210.2 Healthcare IoT Architecture (IoT) 30310.3 Healthcare IoT Technologies 30410.3.1 Technology for Identification 30510.3.2 Location Technology 30610.3.2.1 Mobile-Based IoT 30610.3.2.2 Wearable Devices 30810.3.2.3 Ambient-Assisted Living (AAL) 31410.3.3 Communicative Systems 31510.3.3.1 Radiofrequency Identification 31610.3.3.2 Bluetooth 31610.3.3.3 Zigbee 31710.3.3.4 Near Field Communication 31710.3.3.5 Wireless Fidelity (Wi-Fi) 31810.3.3.6 Satellite Communication 31810.4 Community-Based Healthcare Services 31910.5 Cognitive Computation 32110.6 Adverse Drug Reaction 32310.7 Blockchain 32510.8 Child Health Information 32710.9 Growth in Healthcare IoT 32810.10 Benefits of IoT in Healthcare 32810.11 Conclusion 329References 33011 Detection-Based Visual Object Tracking Based on Enhanced YOLO-Lite and LSTM 339Aayushi Gautam and Sukhwinder Singh11.1 Introduction 34011.2 Related Work 34111.3 Proposed Approach 34311.3.1 Enhanced YOLO-Lite 34411.3.2 Long Short-Term Memory 34611.3.3 Working of Proposed Framework 34711.4 Evaluation Metrics 34911.5 Experimental Results and Discussion 35011.5.1 Implementation Details 35011.5.2 Performance on OTB-2015 35011.5.3 Performance on VOT-2016 35311.5.4 Performance on UAV-123 35411.6 Conclusion 356References 35612 Introduction to AmI and IoT 361Dolly Thankachan12.1 Introduction 36212.1.1 AmI and IoT Characteristics and Definition of Overlaps 36212.1.1.1 Perceptions of “AmI” and the “IoT” 36312.1.2 Prospects and Perils of AmI and the IoT 36412.1.2.1 Assistances and Claim Areas 36412.1.2.2 Intimidations and Contests Relating to AmI and the IoT 36512.2 AmI and the IoT and Environmental and Societal Sustainability: Dangers, Challenges, and Underpinnings 36612.3 Role of AmI and the IoT as New I.C.T.s to Conservational and Social Sustainability 36712.3.1 AmI and the IoT for Environmental Sustainability: Issues, Discernment, and Favoritisms in Tactical Innovation Pursuits 36812.4 The Environmental Influences of AmI and the IoT Technology 36912.4.1 Fundamental Properties 37012.4.2 Boom Properties 37012.4.3 Oblique Outcomes 37112.4.4 Straight Outcome 37212.5 Conclusion 374References 37913 Design of Optimum Construction Site Management Architecture: A Quality Perspective Using Machine Learning Approach 383Kundan Meshram13.1 Introduction 38413.2 Literature Review 38613.3 Proposed Construction Management Model Based on Machine Learning 39013.4 Comparative Analysis 39313.5 Conclusion 395References 396Index 399