Emotional Intelligence-Driven Engineering

Abhishek Kumar, PhD is an Associate Professor in the School of Electronics and Electrical Engineering at Lovely Professional University with more than 11 years of experience. He has published over 55 research papers, five books, and 20 patents, and contributed to numerous conference proceedings and e-books. His research interests include hardware security, cryptanalysis, and machine learning. Suman Lata Tripathi, PhD is a Professor at Lovely Professional University with more than 22 years of experience in academics and research. She has published more than 125 research papers, 27 books, 14 Indian patents, and four copyrights. Her expertise includes microelectronics device modeling, low-power VLSI design, testing, and advanced FET design for IoT. Inung Wijayanto, PhD is an Associate Professor at Telkom University with more than 14 years of experience. He has published over 64 research papers. His research interests include biomedical signal and image processing, EEG/ECG analysis, computer vision, and medical instrumentation. Sugondo Hadiyoso, PhD is a Lecturer at Telkom University with more than 12 years of experience. His expertise includes biomedical engineering, AI, and applied sciences. He has published over 100 research papers and contributes actively to international journals and conferences as a reviewer and committee member.

• Preface xxix1 Exploring Emotional Intelligence in Design Thinking 1Sancheti Dipak D., Chaudhari Rajendra S., Deore Harshal S. and Bora Pradyumna M.1.1 Introduction 21.2 Understanding Emotional Intelligence 31.3 Understanding Design Thinking 51.4 The Importance of Emotional Intelligence in Design Thinking for Engineering Solutions 71.5 Fundamentals of Emotional Intelligence in Design 81.6 Applications and Case Studies 121.7 Challenges and Future Perspectives 151.8 Conclusion 172 Exploring the Integration of Emotion and Engineering: An In-Depth Analysis of Emotional Intelligence in Design and Its Impact on Human-Centered Engineering Practices 23Sancheti Santosh D., Sanghavi Mahesh R., Sanghavi Kainjan M. and Sancheti Dipak D.2.1 Introduction 242.2 Understanding Emotions in Engineering 282.3 Emotional Intelligence in Design 312.4 Human-Centered Engineering Practices 332.5 The Interplay of Emotion and Engineering 362.6 Implications for Engineering Education and Practice 402.7 Conclusion and Future Directions 423 The Integration of Emotion and Engineering 49Abinaya Swathiswaramurthi3.1 Introduction 503.2 Understanding Emotions 513.3 Models and Frameworks for Emotion-Integrated Engineering 533.4 Case Studies and Applications 61Contents vii3.5 Proposed Model 623.6 Experimental Analysis 673.7 Results and Discussion 683.8 Expanding Applications and Future Trends 713.9 Ethical and Societal Implications 784 Emotional Intelligence in AI: Bridging the Gap between Humans and Machines 81Bindu S., Smitha Gayathri D., Prashant M. K. and Mohan Kishore D.4.1 Introduction 824.2 The Significance of Integrating Emotions into AI Systems 854.3 Understanding the Science of Human Emotions 894.4 Computational Models of Emotions and Emotion Recognition Techniques 924.5 Sentiment Analysis and Natural Language Processing (NLP) 954.6 Case Study 1004.7 Risks of Emotionally Manipulative AI 1004.8 Conclusions 1025 Emotionally Intelligent AI Assistants: Machine Learning for Enhanced Human–AI Interaction 107Rahul Kumar Ghosh, Gourab Dutta, Sandip Chakraborty and Subhadip Nandi5.1 Introduction 1085.2 Foundations of Emotionally Intelligent AI 1135.3 Conversational AI and Emotion Recognition 1175.4 Ethical Considerations and Challenges in Emotion AI 1235.5 Case Studies: Real-World Implementations of Emotion AI 1285.6 Future Trends and Research Directions 1315.7 Conclusion 1366 Emotionally Intelligent Assistants with Machine Learning 143Piyal Roy, Shivnath Ghosh, Amitava Podder and Saptarshi Kumar Sarkar6.1 Introduction 1446.2 Foundations of Emotional Intelligence 1486.3 Machine Learning for Emotional Intelligence 1526.4 Data Collection and Preprocessing 1576.5 Building Emotionally Intelligent Assistants 1626.6 Evaluation and Metrics 1656.7 Ethical and Societal Implications 170x Contents6.8 Conclusion and Future Scope 1757 Emotion AI: Advancing Emotional Recognition with Machine Learning 179A. Prabhu Chakkaravarthy, J. Dhanalakshmi and D. Praveena Anjelin7.1 Introduction 1807.2 Related Work 1827.3 Methodology 1867.4 Preprocessing and Feature Engineering 1877.5 Results and Discussion 1897.6 Challenges in Emotion Recognition 1927.7 Applications of Emotion Detection 1927.8 Future Directions 1937.9 Conclusion 1948 Emotion-Sensitive Deep Learning Models 197Reeaa Rana, Diveyam Mishra and Sandeep Kumar Jain8.1 Understanding Emotion Sensitivity 1988.2 Understanding Emotion Data 2008.3 Deep Learning Approach for Emotional Stability 2038.4 Model Architectures and Framework 2058.5 Evaluation Metrics for Emotion-Sensitive Models 2088.6 Challenges and Future Directions 2108.7 Successful Implementations: Context and Value 2128.8 Conclusion 2149 Deep Learning for Emotion Detection: Making Machines Feel 219Manjushree Nayak and Amisha Sukla9.1 Introduction 2209.2 The Heart of Emotion Detection: Key Algorithms 2219.3 Multimodal Emotion Recognition: Unifying Seeing, Hearing, and Reading Emotions 2229.4 Methodology 2249.5 Dataset Overview 2309.6 Result Analysis and Discussion 2319.7 Conclusion 23410 Emotion-Aware AI for Facial Expression Analysis to Enhance Workforce Well-Being in Industry 4.0 241U. Sinthuja, K. Kabilan and R. Meenakshisundaram10.1 Introduction 24210.2 Survey 24610.3 Analyzing the Algorithms of AI for FEI 24810.4 Enhancing the Industry 4.0 Work Environment with Facial Emotion Identification 25210.5 Conclusion 25411 Emotion-Based Music Recommendation System 257Abhishek Kumar11.1 Introduction 25711.2 Related Work 25911.3 System Architecture 26011.4 Emotion Detection Module 26011.5 Emotion Classification 26111.6 Music Metadata Tagging 26111.7 Recommendation Engine 26211.8 Implementation 26211.9 Conclusion 26712 Emotional Sensors: Emotion-Driven IoT 271Subhadip Nandi, Gaurab Dutta and Rahul Kumar Ghosh12.1 Introduction 27212.2 Applications of Emotion-Driven IoT 27312.3 Introduction to Emotion-Driven IoT (EIoT) 27612.4 Technological Foundations 27912.5 AI and ML Techniques in Emotion Classification 28112.6 Proposed Solutions and Advancements 29012.7 Future Research Directions 29013 Neuro-IoT: Merging Brain Signals with Smart Electronics 297Amandeep Kaur, Ramandeep Sandhu, Indu Rani, Gaganpreet Kaur and Deepika Ghai13.1 Introduction 29813.2 Understanding Neuro-IoT 30113.3 Applications of Neuro-IoT 30613.4 Related Work 30913.5 Challenges and Ethical Considerations 31413.6 Technological Advancements 31613.7 Conclusion 32014 Personalized Voice Assistant with Emotional Intelligence Using NLP and GCP 325Bavithra K., Nivetha G., D. Yashwanth Daran and Manasha K. G.14.1 Introduction 32614.2 Literature Survey 327xviii Contents14.3 Objective 32814.4 Existing Methodology 32814.5 Proposed Methodology 33114.6 Research Methodology 33314.7 Packages Used 33514.8 Code Snippets 33714.9 Natural Language Processing (NLP) 33814.10 Result 33814.11 Future Scope 33915 Emotional Algorithms – Machines to Understand Human Feelings 341Madhankumar C.15.1 Defining Emotional AI and Affective Computing 34215.2 Importance of Emotion Recognition in AI-Driven Decision-Making 34215.3 Traditional Rule-Based Sentiment Analysis vs. Deep Learning-Based Affect Recognition 34315.4 Key Challenges in Emotional AI 34415.5 Emerging Trends in Emotional AI 34415.6 Deep Learning and Affective Neural Networks 34615.7 Empathetic AI and Human-Centric Chatbots 349Contents xix15.8 Ethics, Bias, and Privacy in Emotional AI 35015.9 Future Innovations and Applications in Emotional AI 35115.10 AI in Customer Engagement and Personalization 35315.11 Challenges and Research Directions in Emotional AI 36015.12 Final Thoughts 36916 Emotional Indicators in Cybersecurity: Developing a Framework for Early Insider Threat Detection 373Soumya Roy, Kaushik Chanda, Subhadip Nandi and Anudeepa Gon16.1 Introduction 37416.2 Methodology and Implementation 37716.3 Results and Evaluation 37916.4 Comparison with Existing Frameworks 38216.5 Conclusion 38317 The Role of Cobots in Shifting from Automation to Collaboration 387Rajesh Singh, Aashna Sinha, Vivek Kumar Singh and Praveen Kumar Malik17.1 Introduction to Cobots 38817.2 Features of the Cobots 38917.3 The Function of Cobots in Industries 39017.4 Conclusion 39518 Enhancing Quality Control and Predictive Maintenance with Data Insights 399Rajesh Singh, Anita Gehlot, Fraiz Parveen and Praveen Kumar Malik18.1 Introduction 40018.2 Quality Control and Predictive Maintenance 40218.3 Predictive Maintenance Using Machine Learning 40518.4 Case Study 40618.5 Discussion 40718.6 Conclusion 40819 Emotion Detection Using Pre-Trained CNN Models: A Deep Learning Approach with Real-Time Implementation 411Pratyush Rai, Naman Gupta, Aryan Singh, Nagendra Prabhu S. and Arun Kumar19.1 Introduction 41219.2 Literature Assessment 41719.3 Deep Getting to Know and CNN for Emotion Recognition 42619.4 Proposed System Architecture 43019.5 Data Preprocessing and Dataset 43419.6 Applications on the Actual International Usage for Emotion-Based Recognition 44019.7 Data Availability Statement 44219.8 Conclusion 44220 Emotionally Intelligent AI Assistant Powered by Machine Learning and NLP 445Kushagra Purohit, Gaurav Gupta, S. Nagendra Prabhu and Arun Kumar20.1 Introduction 44620.2 Literature Investigation 44720.3 System Analysis 45120.4 Result Analysis 45520.5 Convolutional Neural Network (CNN) 46020.6 Conclusion 46221 Neuro-IoT and Emotion Recognition: Merging Brain Signals with Smart Electronics for Emotionally Intelligent Systems 465Vishal Jain, Archan Mitra and Sanchita Paul21.1 Introduction 46621.2 Literature Review 46921.3 Methodology 47421.4 Findings 47721.5 Discussion 47921.6 Conclusion and Future Work 48122 EmoHeart: Human-Centered First-Emotion Smart IoT Devices for Cardiology 485Abdul Razak Mohamed Sikkander, Suman Lata Tripathi, Joel J. P. C. Rodrigues and Radhakrishnan22.1 Introduction 48622.2 Research Objectives 48822.3 Methodologies 48822.4 Challenges and Obstacles 49322.5 Future Perspectives 49622.6 Conclusions 49823 Natural Bioactive Compounds as Cardioprotective Agents: A Promising Avenue for Heart Health 503Abdul Razak Mohamed Sikkander, Suman Lata Tripathi, Joel J. P. C. Rodrigues, Nitin Wahi, G. Theivanathan and Fatma Bassyouni23.1 Introduction 50423.2 Research and Methodologies 50723.3 Results 52523.4 Conversations 52523.5 Challenges and Obstacles 52923.6 Future Perspectives 53023.7 Conclusions 531References 532Index 539