Hrudaya Kumar Tripathy & Sushruta Mishra 
Optimized Computational Intelligence Driven Decision-Making [EPUB ebook] 
Theory, Application and Challenges

Preface xv

1 Emergence of Advanced Computational Intelligence Coupled with Smart Environment 1
Risha Rani and Tirtha Deb

1.1 Introduction 2

1.2 Background Works 3

1.3 Integrated Smart Environment 4

1.4 Proposed Models for Smart Intelligent Environment 5

1.5 Io T Architecture 16

1.6 Smart Environment and Advanced Computational Intelligence 23

1.7 Advanced Computational Intelligences: Possible Uses in Smart Environment 24

1.8 Conclusion 26

2 Machine Learning-Enabled Integrated Information Platform for Educational Universities 29
Sai Smurti Sahu, Rishav Kumar, Soumya Sahoo, Balwant Kumar and Padmabati Mohanta

2.1 Introduction 30

2.2 Cloud-Based Web Application for University 30

2.3 Integrated Information Platform of Indian Universities Using Machine Learning 36

2.4 Applications Used to Designed This Web Platform 37

2.5 Analysis Result 38

3 False Data Injection Attack Detection Using Machine Learning in Industrial Internet of Things 49
Hafizunisa, Prerna Rai and Damini Sinha

3.1 Introduction 50

3.2 Literature Review 54

3.3 Technical Methodology 56

3.4 Proposed Model for Detecting False Data and its Correction 59

3.5 Complexity Analysis of Proposed Model 63

3.6 Advantages of the Model 64

3.7 Future Scope and Limitations of the Proposed Model 65

3.8 Conclusion 65

4 Fake News Detection: Restricting Spreading of Misinformation Using Machine Learning 69
Shubham Choudhary and Pratyush Mishra

4.1 Introduction 70

4.2 Scope of False News Detection 73

4.3 Main Highlights of the Analysis 73

4.4 A Novel Model for False News Detection 76

4.5 Literature Review 78

4.6 Results and Analysis 80

4.7 Conclusion 81

5 Adaptability, Flexibility, and Accessibility Through Telemedicine 85
Dipti Verma, Somyajyoti Talukdar and Kumari Alankrita Sharma

5.1 Introduction 86

5.2 Related Works 89

5.3 Proposed Model for Remote Health Monitoring System 93

5.3.1 Microcontroller and Sensor 95

5.4 Benefits of the Proposed Model 96

5.5 Constraints of the Proposed Model 98

5.6 Conclusion 101

5.7 Future Works 102

6 Crop Prediction by Implementing Machine Learning in an Io T-Based System 107
Vivian Rawade and Shubham Sahoo

6.1 Introduction 108

6.2 Literature Review 110

6.3 Proposed Model for Crop Prediction 112

6.4 Results and Analysis 123

6.5 Challenges Faced 125

6.6 Advantages of the Proposed Model 127

6.7 Disadvantages of the Proposed Model 127

6.8 Conclusion 128

7 Relevance of Smart Management of Road Traffic System Using Advanced Intelligence 131
Koustab Chowdhury and Rishabh Kapoor

7.1 Introduction 132

7.2 Related Works 135

7.3 Proposed Model of Traffic Management System 139

7.4 Role of AI in Traffic Management 146

7.5 Conclusion and Future Works 148

8 Visualization of Textual Corpora Using Social Network Analysis 151
Indu Rodda and Durga Bhavani S.

8.1 Introduction 152

8.2 Related Literature 154

8.3 Proposed Method 156

8.4 Implementation and Results 163

8.5 Conclusion and Future Work 169

9 Autonomous Intelligent Vehicles: Impact, Current Market, Future Trends, Challenges, and Limitations 173
Kamalanathan Shanmugam, Muhammad Ehsan Rana and Felix Ting Yu Hong

9.1 Introduction 174

9.2 The Global Impact of the AV Industry 176

9.3 Role of Machine Learning in Autonomous Vehicles 177

9.4 Significance of the AV Industry in Various Sectors 179

9.5 Current Market and Future Trends in AV Industry 184

9.6 Challenges and Limitations 189

9.7 Conclusion 192

10 Role of Smart and Predictive Healthcare in Modern Society 195
Muhammad Ehsan Rana and Manoj Jayabalan

10.1 Introduction 196

10.2 Healthcare System 197

10.3 Role of Predictive Analytics in Healthcare 198

10.4 Application of Io T in Healthcare 199

10.5 Io T Based Healthcare Management Framework 200

10.6 Future Recommendations for Research 210

10.7 Conclusion 211

11 An Analytical Study on Depression Detection Using Machine Learning 215
Angelia Melani Adrian and Junaidy Budi Sanger

11.1 Introduction 216

11.2 Literature Survey 217

11.3 Proposed System 220

11.4 Challenges of Machine Learning in Depression Detection 225

11.5 Conclusion and Future Work 226

12 Revolutionizing Healthcare: Empowering Faster Treatment with Io T-Powered Smart Healthcare 229
Prerna Kumari, Rupali Agarwal and Shruti Kumari

12.1 Introduction 230

12.2 Scope/Motivation 233

12.3 Literature Survey 234

12.4 Smart Technology 235

12.5 Methods and Materials 236

12.6 Result 245

12.7 Conclusion 248

13 Machine Learning Algorithms for Initial Diagnosis of Parkinson’s Disease 251
Udayan Das, Manish Jena and Manish Roy

13.1 Overview of Parkinson’s Disease 251

13.2 Scope 254

13.3 Related Works 255

13.4 Comparative Analysis of Parkinson’s Disease 260

13.5 Pros and Cons Using ML Algorithms 267

13.6 Conclusion and Future Works 271

13.7 Bibliography 271

14 Towards a Sustainable Future: Harnessing the Power of Computational Intelligence to Track Climate Change 275
Satyam Sinha, Shreyash Kumar Agnihotri and Oshmita Sarkar

14.1 Introduction 276

14.2 Artificial Intelligence and Climate Change Adaptation 277

14.3 Related Works 278

14.4 Comparative Analysis of Technological Frameworks to Handle Climate Crisis 280

14.5 Future Scope of Climatic Crisis Handling with AI 299

14.6 Conclusion 300

15 Impact of Computational Intelligence and Modeling in Tackling Weather Fluctuation 305
Rohan Karn, Aniket Rouniyar, Ranjit Kumar Das and Amit Gupta

15.1 Introduction 306

15.2 Objective 308

15.3 Causes of Climate Crisis 309

15.4 Significance of AI and Modeling on Climate Crisis 311

15.5 Plastic Waste Detection Model 319

15.6 Forest Fire Prediction Models Using AI 325

15.7 Results 329

15.8 Conclusion 331

References 332

Index 335

Hrudaya Kumar Tripathy, Ph D, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, He has more than 20 years of teaching experience and his research interests include neural networks, pattern recognition, software engineering, machine learning, and big data. He has published several books and research papers in various journals and conferences. Tripathy received the 2013 Young IT Professional Award from the Computer Society of India.
Sushruta Mishra, Ph D, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. He obtained his doctorate in 2017 and his research interests include image processing, machine learning, the Internet of Things, and cognitive computing. He has published 130+ research articles in international journals and conferences.
Minakhi Rout, Ph D, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. She obtained her Ph D in 2015 and her research interests focus on computational finance, data mining, and machine learning. Rout has published 50+ research papers in international journals and conferences.
S. Balamurugan, Ph D, is the Director of Research and Development, Intelligent Research Consultancy Services (i RCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.
Samaresh Mishra, Ph D, is the director of student affairs at KIIT Deemed to be University. He obtained a Ph D in computer science from Utkal University. His research areas focus on software testing, machine learning, and cloud computing. He has published 30+ academic papers.