Emotional Intelligence and Human-Machine Interaction in Advanced Hardware Systems
Editat de Chandra Singh, Rathishchandra R. Gattien Limba Engleză Hardback – 30 aug 2026
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Specificații
Notă biografică
Chandra Singh, PhD, is an Assistant Professor in the Department of Electronics and Communications Engineering at Nitte University. He has published more than eight books, more than 30 papers in international journals, and eight patents. His research interests include optical communication, networking, and wireless communication.
Rathishchandra R. Gatti, PhD, is a Professor and Head of the Department of Mechanical Robots and Engineering at Nitte University. He has published more than seven books, more than 30 papers in international journals, and 15 patents. His research focuses on physical and medical AI and robotics.
Rathishchandra R. Gatti, PhD, is a Professor and Head of the Department of Mechanical Robots and Engineering at Nitte University. He has published more than seven books, more than 30 papers in international journals, and 15 patents. His research focuses on physical and medical AI and robotics.
Cuprins
Preface xxiii
Part I: Foundations of Emotional Intelligence in Technology 1
1 Investigation on Role and Impact of Emotional Intelligence in Industry 5.0 3
M. Al Safreen, P. Vishnu Priya and E. Fantin Irudaya Raj
1.1 Introduction 3
1.2 Role of Emotional Intelligence in Industry 5.0 7
1.3 Integration of EI Technologies in Industry 5.0 7
1.4 Emotional Intelligence and Its Impact in Industry 5.0 9
1.5 Challenges in Integrating Emotional Intelligence in Industry 5.0 13
1.6 Conclusion 17
2 Role of the Internet of Things in Enhancing Emotional Intelligence 21
P. Jeyashri, N. Siddhara and E. Fantin Irudaya Raj
2.1 Introduction 22
2.2 Artificial Intelligence and Machine Learning-An Overview 23
2.3 IoT Applications in Enhancing AI 25
2.4 Emotional Intelligence & IoT in Workspace Applications 32
2.5 Recent Developments and Trends in Emotional Intelligence and the Internet of Things 35
2.6 Conclusion 38
3 Emotional Intelligence in AI-Driven Human-Machine Collaboration 43
Mohammed Shihan Sheikh, Rathishchandra R. Gatti, Mranila P. and Chandra Singh
3.1 Introduction 44
3.2 EI in AI and Its Significance in Human-Machine Collaboration 45
3.3 Development of Emotionally Intelligent AI Interfaces and Supporting Technologies 47
3.4 Enhancing Collaboration, Communication, and Decision Making through EI-Based Systems 51
3.5 Challenges and Future Research Directions 52
3.6 Conclusion 53
4 Brain-Computer Interfaces: Direct Neural Control in Advanced Hardware Systems 57
Shravan Kumar, Shravan Pai, Jeevith B.T. and Rathishchandra R. Gatti
4.1 Introduction 58
4.2 Evolution of BCI Hardware Systems 58
4.3 Advances in BCI Computing 63
4.4 Clinical Applications and Therapeutic Outcomes 65
4.5 Direct Neural Control Mechanisms 69
4.6 Current Challenges and Future Directions 71
4.7 Future Technological Directions 74
4.8 Conclusion 74
Part II: Technologies Enabling Emotional Intelligence in Machines 79
5 Engineering Empathy: Building Machines That Feel 81
Savidhan Shetty C. S. and Manjunatha Badiger
5.1 Introduction 81
5.2 The Role of IoT in Enhancing Emotional Intelligence in Machines 84
5.3 Human Emotions Detection through IoT 85
5.4 Wearable Systems 86
5.5 Problems You Have to Overcome in the Process of Emotional AI 86
5.6 Industrial Applications of Emotional AI and IoT 87
5.7 Underwater Optical Wireless Communication and Emotional AI 88
5.8 Neuroscience and Emotional AI: Understanding the Brain-Emotion Connection 90
5.9 The Skill to Process Emotions from Many Sources of Data 92
5.10 Facial Expression Analysis in AI Systems 94
5.11 Speech Emotion Identification 96
5.12 Healthcare Applications: Emotional AI for Mental Health and Well-Being 97
5.13 Smart Homes and Emotion-Aware IoT Environments 98
5.14 Conclusion 101
6 Machine Learning and Predictive Analytics to Enhance Emotional Intelligence Using IoT in Industrial Systems 105
Sandeep Kumar Hegde, Rajalaxmi Hegde and Thangavel Murugan
6.1 Introduction 106
6.2 Literature Review 110
6.3 Methodology 118
6.4 Experimental Results 123
6.5 Conclusion 130
7 Smart Robotics with Emotional Intelligence: A Fusion of AI, IoT, and ML 135
Dankan Gowda V., Supriya Devi, Sadashiva V. Chakrasali, Kottala Sri Yogi and Mandeep Singh
7.1 Introduction 136
7.2 Background and Motivation 137
7.3 Literature Survey 140
7.4 Machine Learning for Emotional Recognition 144
7.5 Use Cases and Applications 145
7.6 Results and Discussions 146
7.7 Conclusion 153
8 Data-Driven Emotional Intelligence: AI and IoT Synergy in Human-Machine Collaboration 157
Dankan Gowda V., Sadashiva V. Chakrasali, Manoj Kumar S. B., Kottala Sri Yogi and Nidal Al Said
8.1 Introduction 158
8.2 Literature Survey 161
8.3 Key Studies on Emotion Recognition via Facial Expressions, Speech Analysis, and Physiological Signals 162
8.4 AI Models for Emotion Detection and Interaction 163
8.5 IoT and EI 164
8.6 Applications in Human-Machine Collaboration 165
8.7 Results and Discussion 166
8.8 Conclusion 173
9 Integrating AI, IoT, and ML for Seamless Human-Centric Optimization 179
Dankan Gowda V., Kavitha B. C., V. Nuthan Prasad, K.D.V. Prasad and Nidal Al Said
9.1 Introduction 180
9.2 Literature Survey 182
9.3 Proposed Integration Framework 186
9.4 Results and Discussion 191
9.5 Conclusion 198
Part III: Emotional Intelligence in Robotics and Cobots 203
10 AI-Driven Emotional Intelligence in Next-Generation Robotics 205
Babitha Hemanth, Khushi Rai and Harshith K.
10.1 Emotion Recognition in Robotics 206
10.2 Multimodal Emotion Detection Techniques 206
10.3 AI Models for Emotion Recognition 211\
10.4 Challenges and Ethical Considerations in Emotion AI and Robotics 216
11 Emotionally Intelligent Systems: Human-Centered AI for Next-Gen Robotics 221
Smitha Gayathri D., Roopashree C. S., Kumar P. and Santhosh Kumar R.
11.1 Introduction 222
11.2 Fundamentals of Emotional Intelligence in Machines 223
11.3 EI in Robotics 227
11.4 Emotion-Based Assistive System for Active HRI 229
11.5 Multimodal Emotion Detection for System Personalization in HRI 233
11.6 Recursive Emotion Analysis 236
11.7 Experimental Results 240
11.8 Conclusion 242
12 Neurocomputational Models for Emotional Intelligence in Robotics: A Review 247
Shravan Kumar, Shraddha P., Deeksha M. and Rathishchandra R. Gatti
12.1 Introduction 248
12.2 Foundations of EI in Robotics 251
12.3 Neurocomputational Approaches to Emotional Intelligence in Robotics 256
12.4 Applications and Case Studies 263
12.5 Challenges and Open Issues 270
Part IV: Algorithms and Models for Emotion Recognition 291
13 Machine Learning Algorithms for Emotion Recognition in Advanced Hardware 293
Swati Patil, Dankan Gowda V., K.D.V. Prasad, Ved Srinivas and Srinivas D.
13.1 Introduction 294
13.2 Literature Survey 296
13.3 Machine Learning Algorithms for Emotion Recognition 300
13.4 Results and Discussions 305
13.5 Challenges and Limitations 310
13.6 Recent Case Studies 311
13.7 Conclusion 312
14 A New Hybrid Deep Learning Framework for Emotion Recognition Based on ResNet50 and Contextual Features 317
Tanuja Pande, Abhimanyu Dutonde and Anita Yadav
14.1 Introduction 318
14.2 Methodology 321
14.3 Conclusion 330
15 Multiclass Depression Detection Using Bidirectional Hybrid Deep Learning Model 333
Nikhil E. Karale and Vijay S. Gulhane
15.1 Introduction 333
15.2 Literature Survey 335
15.3 Dataset 337
15.4 Methodology 339
15.5 Result and Analysis 341
15.6 Conclusion and Future Scope 343
16 Feature-Evolved Deep Learning for Heart Disease Diagnosis: A Genetic Neural Network Model 345
Shwetha N., Aravind Jadhav, Sangeetha N., Roopesh Ramesh, Rangaswamy Y. and Chandra Singh
16.1 Introduction 346
16.2 Scope of the Work 347
16.3 Proposed Methodology 349
16.4 Software Implementation Requirements 355
16.5 Results and Discussion 356
16.6 Conclusion and Future Scope 369
Part V: Future Systems and Human-Machine Interfaces 373
17 AI-Powered Human-Machine Feedback Systems for Adaptive Interfaces 375
Dankan Gowda V., Kavitha B. C., V. Nuthan Prasad, K.D.V. Prasad and Srinivas D.
17.1 Introduction 376
17.2 Literature Survey 379
17.3 Types of Feedback in Human-Machine Systems 382
17.4 Challenges in Implementing AI for Adaptive Systems 385
17.5 Results and Discussions 386
17.6 Future Directions 392
17.7 Conclusion 393
18 Mental Well-Being of Adolescents: A Comparison of Day School and Boarding School 397
Usha Desai, Susha M. and Raghavan K. P.
18.1 Introduction 398
18.2 Data Collection and Methodology 400
18.3 Outcome and Discussion 403
18.4 Conclusion 410
19 Hippocampus Sclerosis Segmentation by Vanilla U-Net Model Prediction 413
Jayanthi Vajiram, Sivakumar S., Nanditha H.G., Chennagiri Rajarao Padma and Usha Desai
19.1 Introduction 414
19.2 Related Survey 415
19.3 Model Implementations 416
19.4 Methodology 417
19.5 Evaluation Metrics 418
19.6 Results 419
19.7 Conclusion 423
20 Chernoff Bound and Bhattacharyya Bound Feature Ranking Approach for Epilepsy Detection 427
Usha Desai, Roshan J. Martis, Dilna Udayan and Susha M.
20.1 Introduction 428
20.2 Materials and Methodology 430
20.3 Results and Discussion 438
20.4 Conclusion 441
21 Emotional Intelligence Techniques in Humanoid Robotics 445
Rathishchandra R. Gatti
21.1 Introduction 446
21.2 Conceptualizing Emotional Intelligence in Humanoid Robotics 448
21.3 Emotion Recognition Techniques: Sensing Human Affect 449
21.4 Emotion Synthesis and Expression Techniques: Giving Robots Affective Presence 456
21.5 Emotion Modeling and Regulation: Toward Deeper Understanding and Adaptation 461
21.6 Multimodal Approaches: Integrating Affective Channels 463
21.7 Applications of Emotionally Intelligent Humanoid Robots 465
21.8 Challenges and Limitations: Hurdles on the Path to EI 467
21.9 Ethical Considerations: The Moral Landscape of Emotional AI 468
21.10 Future Directions: Charting the Next Wave of Robotic EI 470
21.11 Conclusion 472
22 Enhancing Emotional Intelligence in Industrial Systems Using IoT 475
Srividya P. and Siddharth A.
22.1 Introduction to Emotions 476
22.2 Overview on IoT and IIoT in Industrial Systems 478
22.3 Emotional Intelligence in Industrial Systems 479
22.4 Crucial Aspects of EI in Industrial Systems 480
22.5 IoT-Based EI Framework 481
22.6 Key Technologies Involved in Real-Time Emotion Detection in Industrial Settings 483
22.7 EI and IoT for Enhancing Workplace Productivity and Safety 485
22.8 Applications of EI in Industrial Systems 485
22.9 Enhancement of Emotional Intelligence in Industrial Systems by IoT 486
22.10 Challenges and Considerations 488
22.11 Conclusion 489
23 Integrating Affective Computing in Robotics: Progress and Challenges 491
Spuran Rai, Harshal, Chandra Singh, Deeksha M. and Rathishchandra R. Gatti
23.1 Introduction 492
23.2 Background and Foundations 493
23.3 Technologies Enabling Affective Robotics 497
23.4 Applications of Affective Robotics 500
23.5 Progress and Milestones in Affective Robotics 503
23.6 Challenges in Integrating Affective Computing in Robotics 505
23.7 Ethical and Societal Implications 508
23.8 Conclusion 508
24 Enhancing Career Counseling with the Big Five Personality Traits 511
Minakshi Roy, Kalpana Sharma and Rohit Gupta
24.1 Introduction 512
24.2 Proposed Methodology: Following Steps Shows the Proposed Working Methodology 513
24.3 Data Analysis 515
24.4 Results and Discussion 517
24.5 Conclusion 522
25 Developing Emotional Intelligence of Cobots Using Multimodal LLMs 525
Dhanyashree Acharya, Shraddha P., Shravan Kumar, Deeksha M., Rathishchandra R. Gatti and Chandra Singh
25.1 Background 525
25.2 Key Elements of Emotional Intelligence 531
25.3 Multimodal Large Language Models (LLMs) for Emotional Intelligence 535
References 539
Index 541
Part I: Foundations of Emotional Intelligence in Technology 1
1 Investigation on Role and Impact of Emotional Intelligence in Industry 5.0 3
M. Al Safreen, P. Vishnu Priya and E. Fantin Irudaya Raj
1.1 Introduction 3
1.2 Role of Emotional Intelligence in Industry 5.0 7
1.3 Integration of EI Technologies in Industry 5.0 7
1.4 Emotional Intelligence and Its Impact in Industry 5.0 9
1.5 Challenges in Integrating Emotional Intelligence in Industry 5.0 13
1.6 Conclusion 17
2 Role of the Internet of Things in Enhancing Emotional Intelligence 21
P. Jeyashri, N. Siddhara and E. Fantin Irudaya Raj
2.1 Introduction 22
2.2 Artificial Intelligence and Machine Learning-An Overview 23
2.3 IoT Applications in Enhancing AI 25
2.4 Emotional Intelligence & IoT in Workspace Applications 32
2.5 Recent Developments and Trends in Emotional Intelligence and the Internet of Things 35
2.6 Conclusion 38
3 Emotional Intelligence in AI-Driven Human-Machine Collaboration 43
Mohammed Shihan Sheikh, Rathishchandra R. Gatti, Mranila P. and Chandra Singh
3.1 Introduction 44
3.2 EI in AI and Its Significance in Human-Machine Collaboration 45
3.3 Development of Emotionally Intelligent AI Interfaces and Supporting Technologies 47
3.4 Enhancing Collaboration, Communication, and Decision Making through EI-Based Systems 51
3.5 Challenges and Future Research Directions 52
3.6 Conclusion 53
4 Brain-Computer Interfaces: Direct Neural Control in Advanced Hardware Systems 57
Shravan Kumar, Shravan Pai, Jeevith B.T. and Rathishchandra R. Gatti
4.1 Introduction 58
4.2 Evolution of BCI Hardware Systems 58
4.3 Advances in BCI Computing 63
4.4 Clinical Applications and Therapeutic Outcomes 65
4.5 Direct Neural Control Mechanisms 69
4.6 Current Challenges and Future Directions 71
4.7 Future Technological Directions 74
4.8 Conclusion 74
Part II: Technologies Enabling Emotional Intelligence in Machines 79
5 Engineering Empathy: Building Machines That Feel 81
Savidhan Shetty C. S. and Manjunatha Badiger
5.1 Introduction 81
5.2 The Role of IoT in Enhancing Emotional Intelligence in Machines 84
5.3 Human Emotions Detection through IoT 85
5.4 Wearable Systems 86
5.5 Problems You Have to Overcome in the Process of Emotional AI 86
5.6 Industrial Applications of Emotional AI and IoT 87
5.7 Underwater Optical Wireless Communication and Emotional AI 88
5.8 Neuroscience and Emotional AI: Understanding the Brain-Emotion Connection 90
5.9 The Skill to Process Emotions from Many Sources of Data 92
5.10 Facial Expression Analysis in AI Systems 94
5.11 Speech Emotion Identification 96
5.12 Healthcare Applications: Emotional AI for Mental Health and Well-Being 97
5.13 Smart Homes and Emotion-Aware IoT Environments 98
5.14 Conclusion 101
6 Machine Learning and Predictive Analytics to Enhance Emotional Intelligence Using IoT in Industrial Systems 105
Sandeep Kumar Hegde, Rajalaxmi Hegde and Thangavel Murugan
6.1 Introduction 106
6.2 Literature Review 110
6.3 Methodology 118
6.4 Experimental Results 123
6.5 Conclusion 130
7 Smart Robotics with Emotional Intelligence: A Fusion of AI, IoT, and ML 135
Dankan Gowda V., Supriya Devi, Sadashiva V. Chakrasali, Kottala Sri Yogi and Mandeep Singh
7.1 Introduction 136
7.2 Background and Motivation 137
7.3 Literature Survey 140
7.4 Machine Learning for Emotional Recognition 144
7.5 Use Cases and Applications 145
7.6 Results and Discussions 146
7.7 Conclusion 153
8 Data-Driven Emotional Intelligence: AI and IoT Synergy in Human-Machine Collaboration 157
Dankan Gowda V., Sadashiva V. Chakrasali, Manoj Kumar S. B., Kottala Sri Yogi and Nidal Al Said
8.1 Introduction 158
8.2 Literature Survey 161
8.3 Key Studies on Emotion Recognition via Facial Expressions, Speech Analysis, and Physiological Signals 162
8.4 AI Models for Emotion Detection and Interaction 163
8.5 IoT and EI 164
8.6 Applications in Human-Machine Collaboration 165
8.7 Results and Discussion 166
8.8 Conclusion 173
9 Integrating AI, IoT, and ML for Seamless Human-Centric Optimization 179
Dankan Gowda V., Kavitha B. C., V. Nuthan Prasad, K.D.V. Prasad and Nidal Al Said
9.1 Introduction 180
9.2 Literature Survey 182
9.3 Proposed Integration Framework 186
9.4 Results and Discussion 191
9.5 Conclusion 198
Part III: Emotional Intelligence in Robotics and Cobots 203
10 AI-Driven Emotional Intelligence in Next-Generation Robotics 205
Babitha Hemanth, Khushi Rai and Harshith K.
10.1 Emotion Recognition in Robotics 206
10.2 Multimodal Emotion Detection Techniques 206
10.3 AI Models for Emotion Recognition 211\
10.4 Challenges and Ethical Considerations in Emotion AI and Robotics 216
11 Emotionally Intelligent Systems: Human-Centered AI for Next-Gen Robotics 221
Smitha Gayathri D., Roopashree C. S., Kumar P. and Santhosh Kumar R.
11.1 Introduction 222
11.2 Fundamentals of Emotional Intelligence in Machines 223
11.3 EI in Robotics 227
11.4 Emotion-Based Assistive System for Active HRI 229
11.5 Multimodal Emotion Detection for System Personalization in HRI 233
11.6 Recursive Emotion Analysis 236
11.7 Experimental Results 240
11.8 Conclusion 242
12 Neurocomputational Models for Emotional Intelligence in Robotics: A Review 247
Shravan Kumar, Shraddha P., Deeksha M. and Rathishchandra R. Gatti
12.1 Introduction 248
12.2 Foundations of EI in Robotics 251
12.3 Neurocomputational Approaches to Emotional Intelligence in Robotics 256
12.4 Applications and Case Studies 263
12.5 Challenges and Open Issues 270
Part IV: Algorithms and Models for Emotion Recognition 291
13 Machine Learning Algorithms for Emotion Recognition in Advanced Hardware 293
Swati Patil, Dankan Gowda V., K.D.V. Prasad, Ved Srinivas and Srinivas D.
13.1 Introduction 294
13.2 Literature Survey 296
13.3 Machine Learning Algorithms for Emotion Recognition 300
13.4 Results and Discussions 305
13.5 Challenges and Limitations 310
13.6 Recent Case Studies 311
13.7 Conclusion 312
14 A New Hybrid Deep Learning Framework for Emotion Recognition Based on ResNet50 and Contextual Features 317
Tanuja Pande, Abhimanyu Dutonde and Anita Yadav
14.1 Introduction 318
14.2 Methodology 321
14.3 Conclusion 330
15 Multiclass Depression Detection Using Bidirectional Hybrid Deep Learning Model 333
Nikhil E. Karale and Vijay S. Gulhane
15.1 Introduction 333
15.2 Literature Survey 335
15.3 Dataset 337
15.4 Methodology 339
15.5 Result and Analysis 341
15.6 Conclusion and Future Scope 343
16 Feature-Evolved Deep Learning for Heart Disease Diagnosis: A Genetic Neural Network Model 345
Shwetha N., Aravind Jadhav, Sangeetha N., Roopesh Ramesh, Rangaswamy Y. and Chandra Singh
16.1 Introduction 346
16.2 Scope of the Work 347
16.3 Proposed Methodology 349
16.4 Software Implementation Requirements 355
16.5 Results and Discussion 356
16.6 Conclusion and Future Scope 369
Part V: Future Systems and Human-Machine Interfaces 373
17 AI-Powered Human-Machine Feedback Systems for Adaptive Interfaces 375
Dankan Gowda V., Kavitha B. C., V. Nuthan Prasad, K.D.V. Prasad and Srinivas D.
17.1 Introduction 376
17.2 Literature Survey 379
17.3 Types of Feedback in Human-Machine Systems 382
17.4 Challenges in Implementing AI for Adaptive Systems 385
17.5 Results and Discussions 386
17.6 Future Directions 392
17.7 Conclusion 393
18 Mental Well-Being of Adolescents: A Comparison of Day School and Boarding School 397
Usha Desai, Susha M. and Raghavan K. P.
18.1 Introduction 398
18.2 Data Collection and Methodology 400
18.3 Outcome and Discussion 403
18.4 Conclusion 410
19 Hippocampus Sclerosis Segmentation by Vanilla U-Net Model Prediction 413
Jayanthi Vajiram, Sivakumar S., Nanditha H.G., Chennagiri Rajarao Padma and Usha Desai
19.1 Introduction 414
19.2 Related Survey 415
19.3 Model Implementations 416
19.4 Methodology 417
19.5 Evaluation Metrics 418
19.6 Results 419
19.7 Conclusion 423
20 Chernoff Bound and Bhattacharyya Bound Feature Ranking Approach for Epilepsy Detection 427
Usha Desai, Roshan J. Martis, Dilna Udayan and Susha M.
20.1 Introduction 428
20.2 Materials and Methodology 430
20.3 Results and Discussion 438
20.4 Conclusion 441
21 Emotional Intelligence Techniques in Humanoid Robotics 445
Rathishchandra R. Gatti
21.1 Introduction 446
21.2 Conceptualizing Emotional Intelligence in Humanoid Robotics 448
21.3 Emotion Recognition Techniques: Sensing Human Affect 449
21.4 Emotion Synthesis and Expression Techniques: Giving Robots Affective Presence 456
21.5 Emotion Modeling and Regulation: Toward Deeper Understanding and Adaptation 461
21.6 Multimodal Approaches: Integrating Affective Channels 463
21.7 Applications of Emotionally Intelligent Humanoid Robots 465
21.8 Challenges and Limitations: Hurdles on the Path to EI 467
21.9 Ethical Considerations: The Moral Landscape of Emotional AI 468
21.10 Future Directions: Charting the Next Wave of Robotic EI 470
21.11 Conclusion 472
22 Enhancing Emotional Intelligence in Industrial Systems Using IoT 475
Srividya P. and Siddharth A.
22.1 Introduction to Emotions 476
22.2 Overview on IoT and IIoT in Industrial Systems 478
22.3 Emotional Intelligence in Industrial Systems 479
22.4 Crucial Aspects of EI in Industrial Systems 480
22.5 IoT-Based EI Framework 481
22.6 Key Technologies Involved in Real-Time Emotion Detection in Industrial Settings 483
22.7 EI and IoT for Enhancing Workplace Productivity and Safety 485
22.8 Applications of EI in Industrial Systems 485
22.9 Enhancement of Emotional Intelligence in Industrial Systems by IoT 486
22.10 Challenges and Considerations 488
22.11 Conclusion 489
23 Integrating Affective Computing in Robotics: Progress and Challenges 491
Spuran Rai, Harshal, Chandra Singh, Deeksha M. and Rathishchandra R. Gatti
23.1 Introduction 492
23.2 Background and Foundations 493
23.3 Technologies Enabling Affective Robotics 497
23.4 Applications of Affective Robotics 500
23.5 Progress and Milestones in Affective Robotics 503
23.6 Challenges in Integrating Affective Computing in Robotics 505
23.7 Ethical and Societal Implications 508
23.8 Conclusion 508
24 Enhancing Career Counseling with the Big Five Personality Traits 511
Minakshi Roy, Kalpana Sharma and Rohit Gupta
24.1 Introduction 512
24.2 Proposed Methodology: Following Steps Shows the Proposed Working Methodology 513
24.3 Data Analysis 515
24.4 Results and Discussion 517
24.5 Conclusion 522
25 Developing Emotional Intelligence of Cobots Using Multimodal LLMs 525
Dhanyashree Acharya, Shraddha P., Shravan Kumar, Deeksha M., Rathishchandra R. Gatti and Chandra Singh
25.1 Background 525
25.2 Key Elements of Emotional Intelligence 531
25.3 Multimodal Large Language Models (LLMs) for Emotional Intelligence 535
References 539
Index 541