This book discusses the latest developments in computing techniques that power smart energy and sustainable solutions. Over the last few years, artificial intelligence (AI) has been more deeply embedded in our lives, revolutionizing industries and communication. Intelligent computing models are now transforming traditional energy applications in this digital age through smart automation, optimization, and adaptation. The book addresses major facets of intelligent computing and communication technologies, such as intelligent data analysis, predictive modeling, optimization, neural networks, AI, machine learning, deep learning, and the Internet of Things (IoT). All these technologies are discussed in practical applications, e.g., smart cities and smart industries, their transformative possibilities.

Presents recent research on Artificial Intelligence and Smart Energy Proceedings of the 5th International Conference on Artificial Intelligence and Smart Energy ICAIS 2025 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. 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.

Dr. 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. 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.

Dr. Isidoros Perikos completed his Ph.D. in computer engineering and informatics, Computer Engineering and Informatics Department at University of Patras, Greece (2016), and M.Sc. in computer science and technology, Computer Engineering and Informatics Department at University of Patras (2010). He has completed an engineering diploma (5-year program, M. Eng.) in computer engineering and informatics, Computer Engineering and Informatics Department at University of Patras (2008). His research interests include ontology engineering, web intelligence, natural language processing and understanding, humancomputer interaction, and affective computing robotics. He has published in national and international journals and conferences.

Inhalt

Deep Learning for Fake News Detection: A Review of Multi-Model Approaches In Social Media Contexts.- A Comprehensive Survey on Text Spotting in Natural Images Using Deep Learning.- A Review on Transfer Learning Models for Precise Alzheimer's Disease Stage Identification.- A Review of Artificial Intelligence Techniques in Papaya Leaf Disease Classification.- A study of Graph Neural Network Frameworks and Frontiers.- Avian Census: Real-Time Bird Counting using Region-based Convolutional Neural Network.- Implementation of Fuzzy Optimization in Activity Recognition with deep learning.- ALO-FCE: An Antlion Optimization Based Feature Extraction For Network Traffic Classification Using Fully Connected Autoencoders.- Transforming images into multilingual captions for accessibility and interaction.- ResNet-Defake: Detecting Deepfake Images with Customized ResNet.- AI Driven Food Recognition and Real-Time Pose Estimation for Health Monitoring.- Ensemble-Based DL Model For Predicting And Detecting Diabetic Retinopathy Using Retinal Images.- Leveraging Supervised Learning Algorithms for Automated and Accurate Cattle Disease Diagnosis in Livestock Farming in Somalia.- Video Forgery Detection Using Multi-Scale Feature Extraction with ResNet50.- Smartoutfit: CNN Based Matching for Perfect Outfit Combination.