This book presents a comprehensive collection of research chapters focusing on innovative solutions to energy and sustainability challenges. It reflects the collaborative efforts of researchers worldwide, showcasing novel approaches to complex problems. Topics discussed range from securing cyber-physical systems to revolutionizing healthcare with AI and robotics, emphasizing sustainable research. The book emphasizes smart and sustainable energy solutions, highlighting advancements in solar panel efficiency, fault analysis, and fuzzy-controlled converters for grid-tied photovoltaic systems. Additionally, it explores AI's transformative potential in water solutions, agriculture, and renewable energy technologies across domains like smart cities, transportation, and healthcare. The insights shared aim to inspire further research, foster discussions, and drive real-world impact toward a resilient, inclusive, and sustainable future.
· Discusses issues and offers sustainable solutions to meet the challenges faced by today's economy and industry.
· Presents recent research in the sustainable transformation of engineering and technological systems.
· Serves as a valuable resource for both academic researchers and industry practitioners interested in Artificial Intelligence (AI) and smart energy sectors.

Presents recent research on Artificial Intelligence and Smart Energy Is the proceedings of the 4th International Conference on Artificial Intelligence and Smart Energy ICAIS 2024 Written by experts in the field

Autorentext

Dr S.Manoharan graduated in Electrical and Electronics Engineering in the year 1997 from Government College of Technology, Coimbatore and obtained Master of Engineering in Electrical Machines from PSG College of Technology, Coimbatore in 2004. He pursued his Ph.D at Anna University,Chennai from the year 2006 to 2010 in the area of Electrical Machines and Drives. He has vast experience of 26 years in Academics as well as Administration. He has impressive academic credentials and has vast experience in Research and Development areas. Under his able guideship 11 scholars from Anna University, Chennai are pursuing their Ph.Ds and 10 have been awarded their degree. He has published over 110 + peer-reviewed research papers in prestigious national and international journals, as well as presented papers at national and international conferences. He has written and published over a half-dozen textbooks on Electrical and Electronics topics. He has received grants from DRDO and MNRE for conducting International Conferences. He is on the advisory board of many National and International Conferences and reviewer of many reputed journals. He is the fellow member of Institution of Engineers (India), Member of IEEE, Member of System Society of India and Life member of Indian Society for Technical Education.

Alexandru Tugui is a full professor in the Department of Accounting, Business Informatics, and Statistics at the Alexandru Ioan Cuza University of Iasi, Romania, where he leads innovative research in artificial intelligence (AI), smart economy, and societal transformations. With decades of academic and research experience, he has made significant contributions to the understanding and application of AI, focusing on its limits, societal impacts, and integration into smart technologies. His work has appeared in several prestigious journals, emphasizing the smart economy, calm technology, and technological singularity. As a Ph.D. adviser in business informatics, Tugui mentors the next generation of researchers, combining his deep knowledge of AI with practical insights into smart energy solutions. Tugui's forward-thinking approach and publications in key areas such as Big Data and Cognitive Computing, Sustainability, and Remote Sensing have positioned him as a thought leader in harnessing technology for societal benefit. His commitment to exploring the intersection of AI with smart energy makes him a valuable contributor to discussions on future technological directions and their implications for society and the environment.

Zubair Baig is currently Senior Lecturer in Cyber Security with the School of Information Technology,Deakin University, Geelong, VIC, Australia. He is also Co-director of the Security and Privacy in IoT (SPYRiT) Research Lab and Division Lead, IoT, Critical Infrastructure and CPS Security, and Centre for Cyber Security Research and Innovation (CSRI). He has authored/co-authored over 85 journal and conference papers and book chapters. His research interests are in the areas of cyber-security, the IoT, artificial intelligence, and optimization algorithms. He is serving as Editor for the IET Wireless Sensor Systems Journal and PSU, A Review Journal. He has served on numerous technical program committees of international conferences and has delivered more than 15 keynote talks on cyber-security.

Inhalt

Chapter 1. A Hybrid Machine Learning Approach for Enhanced Prediction of Breast Cancer with Lasso Method for Feature Extraction.- Chapter 2. A Comparative Overview of Deep Learning Aided Image Generation. Chapter 3. Enhancing Pneumonia Detection in Chest X-Rays: A Combined GAN and CNN Approach.- Chapter 4. A Data Driven AI Framework for Conversational Bot by Vision Transformers in Health Care Systems.- Chapter 5. Predictive Modelling of Cardiac Disease: Enhancing Accuracy through Machine Learning Algorithms and Borderline-SMOTE Technique.- Chapter 6. An AI-Driven Model for Decision Support Systems.- Chapter 7. Exploring Music Genres through Facial Emotions: Intelligent Data Processing and Machine Learning.- Chapter 8. Optimizing Cloud Task Scheduling through Innovative Metaheuristic Algorithm and Impulsive Fuzzy C-Means.- Chapter 9. Cirrhosis Patient Survival Prediction Analysis using Ml Algorithms.- Chapter 10. Learnable Discrete Wavelet(LDW) Pooling in CNN for Multidisciplinary Disease Prediction in Healthcare.- Chapter 11. Autonomous Human Computer Interaction System in Windows Environment using YOLO and LLM.- Chapter 12. Deep Learning based Animal Intrusion Detection System.- Chapter 13. Sustainable Crop Monitoring and Management for Enhanced Agricultural Productivity through IoT, AI & ML: Case Studies and Innovations.- Chapter 14. Design of an Auto Evaluation Model for Subjective Answers using Natural Language Processing and Machine Learning Techniques.- Chapter 15. Navigating the Radiological Landscape: A Cutting-Edge Hybrid VGG16-EfficientNet Model for Improved CT Scan Interpretation.- Chapter 16. Optimized Scene Text Detector and Paddle Optical Character Recognizer Techniques to Extract Text from Images.- Chapter 17. A Cost-Sensitive Sparse Auto-Encoder based Feature Extraction for Network Traffic Classification using CNN.-....etc.