Buch, Englisch, 784 Seiten
Leveraging Artificial Intelligence for Smart School Facilities
Buch, Englisch, 784 Seiten
ISBN: 978-1-394-39911-6
Verlag: Wiley
Discover how artificial intelligence is transforming traditional classrooms into responsive, intelligent ecosystems to shape the future of education.
In the rapidly evolving landscape of the 21st century, education stands at a transformative crossroads. Traditional classrooms, long reliant on conventional teaching methods and static infrastructure, are now being reimagined through the lens of innovation, technology, and artificial intelligence. This book explores this dynamic shift and envisions a future where schools are not just centers of learning, but intelligent, responsive ecosystems that adapt to the needs of every student and educator. This book recognizes that the challenges faced by modern educational institutions can no longer be addressed using outdated models. Artificial intelligence offers unprecedented opportunities to enhance how Universities and schools function, teach, and evolve. From intelligent classroom assistants and predictive analytics to energy-efficient systems and student behavior monitoring, AI is already reshaping the foundation of academic environments. In this book, we consider not only technological advancements but also the ethical implications, implementation challenges, and future influence of this emerging technology. This essential resource inspires educators, policymakers, researchers, and technologists to collaborate in building educational spaces that are inclusive, innovative, and intelligent.
Readers will find the volume: - Discusses the potential of artificial intelligence that can help in increasing the effectiveness of instructors through various AI applications such as text translation systems, real-time message-to-speech, and automation of mundane and repeated jobs;
- Details how AI helps to eliminate manual administration work in schools, colleges, and universities and deliver personalized learning and intelligent tutoring to students;
- Demonstrates how AI-powered educational technology encompasses tools for teachers, students, and administrators such as educational games, adaptive learning platforms, chatbots and intelligent tutoring systems;
- Offers real-world uses of latest technologies in different AI-based systems to further study its influence in innovative teaching and learning initiatives.
Audience
Educational Tech researchers and policymakers, educators, and professionals researching new ways to create individualized learning plans for student success.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface xxix
Acknowledgments xxxi
Part 1: Fundamentals 1
1 Introduction to AI-Driven Smart Facilities for Modern Schools 3
Atchaya M., B. Nandhitha, Praveen Joe I. R. and Vijay John
1.1 Introduction 4
1.2 Historical Context of Technology in Education 9
1.3 Digital Transformation in Schools: Challenges and Opportunities 16
1.4 The Role of AI in Modernizing Educational Environments 20
1.5 Overview of Intelligent School Facility Design 26
1.6 Conclusion 30
2 AI-Driven Smart Facilities for Modern Schools in Today's Era 35
D. Kalaiabirami, M. Marikkannan, S.D. Prabu Ragavendiran, K. Sumathi and S. Ramesh
2.1 Introduction to AI-Driven Smart Facilities 36
2.2 Digital Transformation in Schools 46
2.3 Intelligent School Facility Design 50
2.4 Components of Modern School 56
2.5 Integrating Future Work Skills 59
2.6 Comparison between Traditional and Modern Education Systems 59
2.7 Conclusion 62
3 Understanding AI Technologies and Smart Systems 65
R. Felista Sugirtha Lizy, R. Vadivukarasi, Punit Pathak and Gusti Bagus Yosia Wiryakusuma
3.1 Introduction 66
3.2 Related Works 68
3.3 AI Technologies in Machine Learning 72
3.4 AI Technologies in Computer Vision 76
3.5 The Internet of Things (IoT) in Educational Facilities 79
3.6 Data Analytics and Predictive Modeling in AI and Smart Systems 80
3.7 Integrating AI with Existing Educational Infrastructure 81
3.8 Applications of Machine Learning 82
3.9 Challenges and Future of Machine Learning 83
3.10 Future Trends in AI and Smart Systems 86
3.11 Conclusion and Future Work 91
4 A Comprehensive System for Multi-Source Content Extraction and Question Generation with LLM Validation 95
Suresh Manic K., Ahmed Al-Balushi, Al-Bemani, A.S., Saleh Alaraimi, Balaji G., Asiya Najeeb and Uma Suresh
4.1 Introduction 96
4.2 Literature Review 97
4.3 Methodology 100
4.4 Implementation and Results 108
4.5 Conclusion 113
4.6 Future Work 114
5 AI-Driven Analytics for Student Performance and Behavior 117
Mohan Singh, Seema Singh, Kapil Dev Tyagi and Vaibhav Bhushan Tyagi
5.1 Introduction 118
5.2 Understanding AI-Driven Analytics in Education 122
5.3 Applications of AI in Student Performance Analytics 124
5.4 Artificial Intelligence in Behavioral Analysis for Students 127
5.5 Data Sources and AI Techniques 129
5.6 Case Studies and Real-World Implementations 133
5.7 Challenges and Ethical Considerations 13
5.8 Future Trends and Innovations 140
5.9 Conclusion 143
6 Few-Shot Learning and Zero-Shot Learning Paradigms 147
Shrikant Tiwari, Kanchan Naithani, Vinay Dwivedi and Ramesh Wadawadagi
6.1 Introduction 148
6.2 Foundations of Machine Learning 150
6.3 Few-Shot Learning 156
6.4 Zero-Shot Learning 164
6.5 Hybrid Approaches 170
6.6 Few-Shot and Zero-Shot Learning in Computer Vision 177
6.7 Conclusion 182
7 Future of Human-AI Interaction in Education 189
Perarasi T., Manoj R., Deepika M., Kishore Bingi and Ramkumar R.
7.1 Introduction 190
7.2 AI as a Collaborative Partner in Education 191
7.3 Envisioning AI-Enhanced Hybrid Classrooms 193
7.4 AI-Driven Virtual and Augmented Reality in Learning 197
7.5 Social and Emotional Dimensions of AI in Learning 201
7.6 Building Human-AI Trust into the Learning Process 202
7.7 The Impact of AI on Student Collaboration and Peer Learning 206
7.8 AI in Inclusive Education for Special Needs 210
7.9 Conclusion 212
8 Leveraging Generative AI for Computer Science Education 217
M. K. Abiodun, Amit Kumar Tyagi, J. B. Awotunde, A. E. Adeniyi, D. R. Aremu and S. Ejimogu
8.1 Introduction 218
8.2 Related Works 219
8.3 Proposed Solution 227
8.4 Implementation and Results 234
8.5 Conclusion and Future Work 244
9 Personalized Learning Environments in AI-Driven Smart Facilities for Modern Schools 249
Vidish Kumar, Garima Jain, Ankush Jain and Sanny Kumar
9.1 Introduction 250
9.2 Dynamic Classroom Configurations through AI 251
9.3 AI-Enabled Adaptive Learning Spaces 253
9.4 Merging Physical and Virtual Learning: Blended Models 255
9.5 AI-Driven AR/VR Experiential Learning 256
9.6 Methodology and Implementation 258
9.7 Expanded Case Studies and Data Analysis 261
9.8 Conclusion and Future Directions 264
10 Smart Classroom Using AI-Experimental Analysis 269
Swathi Gowroju, S. Sowjanya Chintalapati, B. Suresh Babu and Fateh Mebarek-Oudina
10.1 Introduction 270
10.2 Literature Survey 271
10.3 Proposed System 274
10.4 Proposed Architecture 276
10.5 Analysis and Results 280
10.6 Discussion 288
10.7 Conclusion 289
Part 2: Methods and Principles 291
11 Gamification and AI-Driven Engagement Tools 293
S.S. Sivaraju, B. Shuriya, Prabhu D., P. Vetrivelan, S. Sridharan and Ismail Musirin
11.1 Introduction 294
11.2 The Role of Gamification in Education 294
11.3 AI-Driven Engagement Tools in Education 300
11.4 Enacting AI-Driven Gamification in Learning Environments 310
11.5 Future Opportunities and Challenges 315
12 AI for Student Engagement and Motivation 319
Jimit Patel, Meet Patel and Aniket Patel
12.1 Introduction 319
12.2 Related Works 321
12.3 Case Studies: Increasing Engagement with AI 331
12.4 Conclusion and Future Work 335
13 Hardware and Firmware Design of a Smart Classroom Automation System 339
Naman Tanwar, Monish Kumar H. S., Mohit Banka, Sushmit Sanskar, Vidhya S. and Konguvel E.
13.1 Introduction 339
13.2 Related Works 341
13.3 Hardware Design 343
13.4 Firmware Design 355
13.5 Results and Discussions 362
13.6 Future Improvements 365
13.7 Conclusion 365
14 Internal Service Quality in Higher Education: Exploring Key Determinants and Implications 369
Parthiban R. and Shefali Srivastava
14.1 Introduction 370
14.2 Theoretical Framework and Hypothesis Development 372
14.3 Research Methodology 380
14.4 Result 387
14.5 Discussion 398
14.6 Conclusion 402
Part 3: Applications 413
15 Role of Artificial Intelligence in the Development of Education Industry 4.0: A Systematic Review 415
Aashka Thakkar, Axita Thakkar and Tsegaye Mayhewos
15.1 Introduction 416
15.2 Bibliometric Literature Review 418
15.3 The Need if Integration of AI in Higher Education 421
15.4 Usage of AI Tools for Education 423
15.5 Increasing Role of AI in Personalized Education 427
15.6 Challenges of Using AI in Education 4.0 429
15.7 Why AI and Education Should Go Hand in Hand 431
16 Generative AI Technologies, Models and Applications 437
Shruti Mehra and Avinash Kumar Sharma
16.1 Introduction 438
16.2 Literature Review 440
16.3 Generative AI Technologies 444
16.4 Transformer-Based Models for Generation 454
16.5 Applications of Generative AI 464
16.6 Conclusion 466
17 Machine Learning and Deep Learning-Based Intelligent Tutoring Systems 469
Vikram Singh, Sangeeta Rani and Sanjay Singh
17.1 Intelligent Tutoring Systems 470
17.2 Related Works 472
17.3 Learner Profiling Model 476
17.4 Question-Topic Mapping Model 484
17.5 A Framework for ITS 488
17.6 Conclusion 494
18 Integrating Digital Twin for Acquiring Smart Classroom Facilities to Enhance Teaching-Learning Process 499
Ramya Perumal, Kaladevi A.C. and V. Lathika
18.1 Introduction 500
18.2 General Framework for Digital Twin 507
18.3 Creating Digital Twins for School Buildings and Classrooms 513
18.4 Predictive Maintenance and Real-Time Facility Management 519
18.5 Simulating Learning Environments for Research and Training 521
18.6 Future Potentials of Using Digital Twins in the Education Domain 526
18.7 Conclusion 527
19 Bridging Realities with AI-Enabled Software Development: Generative AI, Digital Twins, and the Future of Privacy 531
Yashendra Rajput, M.H. Razi and Avinash Kumar Sharma
19.1 Introduction 532
19.2 The Rise of AI in Software Development 534
19.3 Generative AI: Powering the Code Revolution 539
19.4 Digital Twins: Simulating Reality in Real Time 541
19.5 The Future of AI-Enhanced Software Development 549
19.6 Conclusion 552
Part 4: Challenges and Future Research Directions 557
20 Beyond the AI Hype: Practical and Ethical Dimensions of AI in Education 559
Ashu Verma, Anushka Gupta and Amit Kumar Tyagi
20.1 Introduction 560
20.2 Background Work 562
20.3 Literature Review 564
20.4 Problem Definition 571
20.5 Objectives 572
20.6 Comparative Analysis of Literatures 572
20.7 Proposed Solution 575
20.8 Discussion 577
20.9 Limitations and Future Work 579
20.10 Conclusion 579
21 Emotion-Driven Music Recommendations Using Speech Recognition and an Interactive Gradio Interface for Personalized Content Delivery 583
Rukmani P and Rachana Supriya Nandipati
21.1 Introduction 584
21.2 Related Work 585
21.3 Existing Work 587
21.4 Proposed Work 588
21.5 Methodology 590
21.6 Evaluation Metrics 599
21.7 Results and Discussion 602
21.8 Conclusion 607
21.9 Challenges and Future Scope 608
22 Transforming Students into Ethical Leaders through AI-Enhanced Pedagogical Practices and a Model for the Future of Education 611
P. Kiruthika, D. Sivabalaselvamani, D. Selvakarthi and Ranjit Singh Sarban Singh
22.1 Introduction 612
22.2 Related Works 615
22.3 Transforming Education through AI Enhanced Outcome Based Learning 623
22.4 Implementation 626
22.5 Academic Performance 630
22.6 Conclusion and Future Work 635
23 Artificial Intelligence - Natural Language Processing Based Business Intelligence 639
Pooja Bhatt, Shabnam Kumari and Amit Kumar Tyagi
23.1 Introduction to Business Intelligence 640
23.2 Foundations of NLP in Business Intelligence 642
23.3 Applications of NLP in Business Intelligence 646
23.4 NLP Techniques for Data Preparation and Analysis 649
23.5 Implementation Strategies for NLP-Based BI 650
23.6 Open Issues and Challenges and Future Directions for NLP Based BI 652
23.7 Conclusion 654
24 Securing the Modern World Using AI-Based Quantum Computing 659
D. Kalaiabirami, M. Marikkannan and K. Sumathi
24.1 Introduction to AI-Based Quantum Security 660
24.2 Fundamentals of Quantum Security 663
24.3 AI's Role in Quantum Security 666
24.4 Applications of AI-Based Quantum Security 671
24.5 Detecting and Responding to Threats Using AI and Quantum Computing 674
24.6 Challenges and Future Directions 676
24.7 Conclusion 681
25 AI in Security and Safety Management 685
R. Felista Sugirtha Lizy, R. Vadivukarasi, Punit Pathak and Ir. Bambang Sugiyono Agus Purwono
25.1 Introduction to AI in Security and Safety Management 686
25.2 Literature Review: AI in Security and Safety Management 690
25.3 AI in Cybersecurity 692
25.4 AI in Physical Security 696
25.5 AI in Workplace Safety 699
25.6 Ethical and Legal Challenges of AI in Security and Safety 704
25.7 Conclusion 706
26 The Future of Intelligent School Facilities: Emerging AI Technologies in Education 709
S. Umamageswari, L. Sangeetha, V. Shyamala Susan and I Gusti Bagus Yosia Wiryakusuma
26.1 Introduction 710
26.2 Literature Review: The Evolution of AI in Education 711
26.3 The Role of AR, VR, and XR in Transforming Education 712
26.4 Benefits of AI and Smart Learning Technologies in Education 714
26.5 AI in School Facility Management 716
26.6 Challenges and Barriers to the Integration of AI and Smart Technologies in Education 723
26.7 Future Directions for AI and Smart Learning Technology 728
26.8 Conclusion 733
References 734
Index 739
