{"product_id":"emotional-intelligence-driven-engineering-hardback-9781394389865","title":"Emotional Intelligence-Driven Engineering (Hardback) 9781394389865","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eEmotional Intelligence-Driven Engineering\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eAbhishek Kumar (Edited by), Kumar (Author), Suman Lata Tripathi (Edited by), Inung Wijayanto (Edited by), Sugondo Hadiyoso (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394389865, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 23 June 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e592 pages\u003cbr\u003e25 x 15 x 1.5 cm, 0.666 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eIn a digital age where technical expertise is no longer enough, this book provides the essential tools to integrate empathy, psychology, and neuroscience into your design process for a deeper human-technology connection. \u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eEngineering has traditionally prioritized functional and technical factors, enhancing equipment for reliability, effectiveness, and efficiency. However, a dramatic perspective shift is changing the way technologies are created, developed, and implemented, as well as how we interact with them. This book provides an innovative perspective on the design and development of systems, services, and products by investigating the significant confluence of engineering, technology, and emotional intelligence. In the growing digital age of today, technological expertise is no longer sufficient to satisfy the wide range of consumer demands. It is equally important to comprehend, predict, and account for human emotion. This book incorporates the interdisciplinary method known as emotion-driven engineering, which includes emotional intelligence in the design, development, and implementation of engineering solutions. Based on disciplines including human-computer interface, design thinking, psychology, and neuroscience. This book provides an efficient framework for developing products that connect with consumers. With both theoretical ideas and practical applications, the book is organized to help engineers, designers, and technologists integrate emotional awareness and empathy into their work.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xxix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Exploring Emotional Intelligence in Design Thinking 1\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSancheti Dipak D., Chaudhari Rajendra S., Deore Harshal S. and Bora Pradyumna M.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003cbr\u003e1.2 Understanding Emotional Intelligence 3\u003cbr\u003e1.3 Understanding Design Thinking 5\u003cbr\u003e1.4 The Importance of Emotional Intelligence in Design Thinking for Engineering Solutions 7\u003cbr\u003e1.5 Fundamentals of Emotional Intelligence in Design 8\u003cbr\u003e1.6 Applications and Case Studies 12\u003cbr\u003e1.7 Challenges and Future Perspectives 15\u003cbr\u003e1.8 Conclusion 17\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Exploring the Integration of Emotion and Engineering: An In-Depth Analysis of Emotional Intelligence in Design and Its Impact on Human-Centered Engineering Practices 23\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSancheti Santosh D., Sanghavi Mahesh R., Sanghavi Kainjan M. and Sancheti Dipak D.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 24\u003cbr\u003e2.2 Understanding Emotions in Engineering 28\u003cbr\u003e2.3 Emotional Intelligence in Design 31\u003cbr\u003e2.4 Human-Centered Engineering Practices 33\u003cbr\u003e2.5 The Interplay of Emotion and Engineering 36\u003cbr\u003e2.6 Implications for Engineering Education and Practice 40\u003cbr\u003e2.7 Conclusion and Future Directions 42\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 The Integration of Emotion and Engineering 49\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAbinaya Swathiswaramurthi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 50\u003cbr\u003e3.2 Understanding Emotions 51\u003cbr\u003e3.3 Models and Frameworks for Emotion-Integrated Engineering 53\u003cbr\u003e3.4 Case Studies and Applications 61Contents vii\u003cbr\u003e3.5 Proposed Model 62\u003cbr\u003e3.6 Experimental Analysis 67\u003cbr\u003e3.7 Results and Discussion 68\u003cbr\u003e3.8 Expanding Applications and Future Trends 71\u003cbr\u003e3.9 Ethical and Societal Implications 78\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Emotional Intelligence in AI: Bridging the Gap between Humans and Machines 81\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eBindu S., Smitha Gayathri D., Prashant M. K. and Mohan Kishore D.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 82\u003cbr\u003e4.2 The Significance of Integrating Emotions into AI Systems 85\u003cbr\u003e4.3 Understanding the Science of Human Emotions 89\u003cbr\u003e4.4 Computational Models of Emotions and Emotion Recognition Techniques 92\u003cbr\u003e4.5 Sentiment Analysis and Natural Language Processing (NLP) 95\u003cbr\u003e4.6 Case Study 100\u003cbr\u003e4.7 Risks of Emotionally Manipulative AI 100\u003cbr\u003e4.8 Conclusions 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Emotionally Intelligent AI Assistants: Machine Learning for Enhanced Human–AI Interaction 107\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRahul Kumar Ghosh, Gourab Dutta, Sandip Chakraborty and Subhadip Nandi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 108\u003cbr\u003e5.2 Foundations of Emotionally Intelligent AI 113\u003cbr\u003e5.3 Conversational AI and Emotion Recognition 117\u003cbr\u003e5.4 Ethical Considerations and Challenges in Emotion AI 123\u003cbr\u003e5.5 Case Studies: Real-World Implementations of Emotion AI 128\u003cbr\u003e5.6 Future Trends and Research Directions 131\u003cbr\u003e5.7 Conclusion 136\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Emotionally Intelligent Assistants with Machine Learning 143\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePiyal Roy, Shivnath Ghosh, Amitava Podder and Saptarshi Kumar Sarkar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 144\u003cbr\u003e6.2 Foundations of Emotional Intelligence 148\u003cbr\u003e6.3 Machine Learning for Emotional Intelligence 152\u003cbr\u003e6.4 Data Collection and Preprocessing 157\u003cbr\u003e6.5 Building Emotionally Intelligent Assistants 162\u003cbr\u003e6.6 Evaluation and Metrics 165\u003cbr\u003e6.7 Ethical and Societal Implications 170x Contents\u003cbr\u003e6.8 Conclusion and Future Scope 175\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Emotion AI: Advancing Emotional Recognition with Machine Learning 179\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eA. Prabhu Chakkaravarthy, J. Dhanalakshmi and D. Praveena Anjelin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 180\u003cbr\u003e7.2 Related Work 182\u003cbr\u003e7.3 Methodology 186\u003cbr\u003e7.4 Preprocessing and Feature Engineering 187\u003cbr\u003e7.5 Results and Discussion 189\u003cbr\u003e7.6 Challenges in Emotion Recognition 192\u003cbr\u003e7.7 Applications of Emotion Detection 192\u003cbr\u003e7.8 Future Directions 193\u003cbr\u003e7.9 Conclusion 194\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Emotion-Sensitive Deep Learning Models 197\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eReeaa Rana, Diveyam Mishra and Sandeep Kumar Jain\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Understanding Emotion Sensitivity 198\u003cbr\u003e8.2 Understanding Emotion Data 200\u003cbr\u003e8.3 Deep Learning Approach for Emotional Stability 203\u003cbr\u003e8.4 Model Architectures and Framework 205\u003cbr\u003e8.5 Evaluation Metrics for Emotion-Sensitive Models 208\u003cbr\u003e8.6 Challenges and Future Directions 210\u003cbr\u003e8.7 Successful Implementations: Context and Value 212\u003cbr\u003e8.8 Conclusion 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Deep Learning for Emotion Detection: Making Machines Feel 219\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eManjushree Nayak and Amisha Sukla\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 220\u003cbr\u003e9.2 The Heart of Emotion Detection: Key Algorithms 221\u003cbr\u003e9.3 Multimodal Emotion Recognition: Unifying Seeing, Hearing, and Reading Emotions 222\u003cbr\u003e9.4 Methodology 224\u003cbr\u003e9.5 Dataset Overview 230\u003cbr\u003e9.6 Result Analysis and Discussion 231\u003cbr\u003e9.7 Conclusion 234\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Emotion-Aware AI for Facial Expression Analysis to Enhance Workforce Well-Being in Industry 4.0 241\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eU. Sinthuja, K. Kabilan and R. Meenakshisundaram\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 242\u003cbr\u003e10.2 Survey 246\u003cbr\u003e10.3 Analyzing the Algorithms of AI for FEI 248\u003cbr\u003e10.4 Enhancing the Industry 4.0 Work Environment with Facial Emotion Identification 252\u003cbr\u003e10.5 Conclusion 254\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Emotion-Based Music Recommendation System 257\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAbhishek Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 257\u003cbr\u003e11.2 Related Work 259\u003cbr\u003e11.3 System Architecture 260\u003cbr\u003e11.4 Emotion Detection Module 260\u003cbr\u003e11.5 Emotion Classification 261\u003cbr\u003e11.6 Music Metadata Tagging 261\u003cbr\u003e11.7 Recommendation Engine 262\u003cbr\u003e11.8 Implementation 262\u003cbr\u003e11.9 Conclusion 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Emotional Sensors: Emotion-Driven IoT 271\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSubhadip Nandi, Gaurab Dutta and Rahul Kumar Ghosh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 272\u003cbr\u003e12.2 Applications of Emotion-Driven IoT 273\u003cbr\u003e12.3 Introduction to Emotion-Driven IoT (EIoT) 276\u003cbr\u003e12.4 Technological Foundations 279\u003cbr\u003e12.5 AI and ML Techniques in Emotion Classification 281\u003cbr\u003e12.6 Proposed Solutions and Advancements 290\u003cbr\u003e12.7 Future Research Directions 290\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Neuro-IoT: Merging Brain Signals with Smart Electronics 297\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAmandeep Kaur, Ramandeep Sandhu, Indu Rani, Gaganpreet Kaur and Deepika Ghai\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 298\u003cbr\u003e13.2 Understanding Neuro-IoT 301\u003cbr\u003e13.3 Applications of Neuro-IoT 306\u003cbr\u003e13.4 Related Work 309\u003cbr\u003e13.5 Challenges and Ethical Considerations 314\u003cbr\u003e13.6 Technological Advancements 316\u003cbr\u003e13.7 Conclusion 320\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Personalized Voice Assistant with Emotional Intelligence Using NLP and GCP 325\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eBavithra K., Nivetha G., D. Yashwanth Daran and Manasha K. G.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 326\u003cbr\u003e14.2 Literature Survey 327xviii Contents\u003cbr\u003e14.3 Objective 328\u003cbr\u003e14.4 Existing Methodology 328\u003cbr\u003e14.5 Proposed Methodology 331\u003cbr\u003e14.6 Research Methodology 333\u003cbr\u003e14.7 Packages Used 335\u003cbr\u003e14.8 Code Snippets 337\u003cbr\u003e14.9 Natural Language Processing (NLP) 338\u003cbr\u003e14.10 Result 338\u003cbr\u003e14.11 Future Scope 339\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Emotional Algorithms – Machines to Understand Human Feelings 341\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eMadhankumar C.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Defining Emotional AI and Affective Computing 342\u003cbr\u003e15.2 Importance of Emotion Recognition in AI-Driven Decision-Making 342\u003cbr\u003e15.3 Traditional Rule-Based Sentiment Analysis vs. Deep Learning-Based Affect Recognition 343\u003cbr\u003e15.4 Key Challenges in Emotional AI 344\u003cbr\u003e15.5 Emerging Trends in Emotional AI 344\u003cbr\u003e15.6 Deep Learning and Affective Neural Networks 346\u003cbr\u003e15.7 Empathetic AI and Human-Centric Chatbots 349Contents xix\u003cbr\u003e15.8 Ethics, Bias, and Privacy in Emotional AI 350\u003cbr\u003e15.9 Future Innovations and Applications in Emotional AI 351\u003cbr\u003e15.10 AI in Customer Engagement and Personalization 353\u003cbr\u003e15.11 Challenges and Research Directions in Emotional AI 360\u003cbr\u003e15.12 Final Thoughts 369\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Emotional Indicators in Cybersecurity: Developing a Framework for Early Insider Threat Detection 373\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSoumya Roy, Kaushik Chanda, Subhadip Nandi and Anudeepa Gon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 374\u003cbr\u003e16.2 Methodology and Implementation 377\u003cbr\u003e16.3 Results and Evaluation 379\u003cbr\u003e16.4 Comparison with Existing Frameworks 382\u003cbr\u003e16.5 Conclusion 383\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 The Role of Cobots in Shifting from Automation to Collaboration 387\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRajesh Singh, Aashna Sinha, Vivek Kumar Singh and Praveen Kumar Malik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction to Cobots 388\u003cbr\u003e17.2 Features of the Cobots 389\u003cbr\u003e17.3 The Function of Cobots in Industries 390\u003cbr\u003e17.4 Conclusion 395\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Enhancing Quality Control and Predictive Maintenance with Data Insights 399\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRajesh Singh, Anita Gehlot, Fraiz Parveen and Praveen Kumar Malik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 400\u003cbr\u003e18.2 Quality Control and Predictive Maintenance 402\u003cbr\u003e18.3 Predictive Maintenance Using Machine Learning 405\u003cbr\u003e18.4 Case Study 406\u003cbr\u003e18.5 Discussion 407\u003cbr\u003e18.6 Conclusion 408\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Emotion Detection Using Pre-Trained CNN Models: A Deep Learning Approach with Real-Time Implementation 411\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePratyush Rai, Naman Gupta, Aryan Singh, Nagendra Prabhu S. and Arun Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 412\u003cbr\u003e19.2 Literature Assessment 417\u003cbr\u003e19.3 Deep Getting to Know and CNN for Emotion Recognition 426\u003cbr\u003e19.4 Proposed System Architecture 430\u003cbr\u003e19.5 Data Preprocessing and Dataset 434\u003cbr\u003e19.6 Applications on the Actual International Usage for Emotion-Based Recognition 440\u003cbr\u003e19.7 Data Availability Statement 442\u003cbr\u003e19.8 Conclusion 442\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Emotionally Intelligent AI Assistant Powered by Machine Learning and NLP 445\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eKushagra Purohit, Gaurav Gupta, S. Nagendra Prabhu and Arun Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 446\u003cbr\u003e20.2 Literature Investigation 447\u003cbr\u003e20.3 System Analysis 451\u003cbr\u003e20.4 Result Analysis 455\u003cbr\u003e20.5 Convolutional Neural Network (CNN) 460\u003cbr\u003e20.6 Conclusion 462\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Neuro-IoT and Emotion Recognition: Merging Brain Signals with Smart Electronics for Emotionally Intelligent Systems 465\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eVishal Jain, Archan Mitra and Sanchita Paul\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 466\u003cbr\u003e21.2 Literature Review 469\u003cbr\u003e21.3 Methodology 474\u003cbr\u003e21.4 Findings 477\u003cbr\u003e21.5 Discussion 479\u003cbr\u003e21.6 Conclusion and Future Work 481\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 EmoHeart: Human-Centered First-Emotion Smart IoT Devices for Cardiology 485\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAbdul Razak Mohamed Sikkander, Suman Lata Tripathi, Joel J. P. C. Rodrigues and Radhakrishnan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 486\u003cbr\u003e22.2 Research Objectives 488\u003cbr\u003e22.3 Methodologies 488\u003cbr\u003e22.4 Challenges and Obstacles 493\u003cbr\u003e22.5 Future Perspectives 496\u003cbr\u003e22.6 Conclusions 498\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 Natural Bioactive Compounds as Cardioprotective Agents: A Promising Avenue for Heart Health 503\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAbdul Razak Mohamed Sikkander, Suman Lata Tripathi, Joel J. P. C. Rodrigues, Nitin Wahi, G. Theivanathan and Fatma Bassyouni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 504\u003cbr\u003e23.2 Research and Methodologies 507\u003cbr\u003e23.3 Results 525\u003cbr\u003e23.4 Conversations 525\u003cbr\u003e23.5 Challenges and Obstacles 529\u003cbr\u003e23.6 Future Perspectives 530\u003cbr\u003e23.7 Conclusions 531\u003c\/p\u003e \u003cp\u003eReferences 532\u003cbr\u003eIndex 539\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433828675864,"sku":"9781394389865","price":147.88,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394389865.jpg?v=1784854485","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/emotional-intelligence-driven-engineering-hardback-9781394389865","provider":"Freshly Printed Books","version":"1.0","type":"link"}