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(Academy of Maritime Education and Training, India)
Dr.R.K.Padmashini is an Associate professor in the Department of Electrical and Electronics Engineering at Academy of Maritime Education and Training Deemed to be university, Chennai, Tamil Nadu, India. She is having 12.9 years of Teaching, Joined AMET University in 2018 and working as Assistant professor in the Dept of Electrical and Electronics Engineering. Areas of interests are: Speed control of Electrical systems, Propulsion systems, and control systems .AI based Renewable Energy Forecasting. Educational Qualifications Ph.D. Renewable Energy system (2024), M.E Power Electronics & Drives (2008), B.E Electrical and Electronics Engineering (2005). She published more than 25 papers in reputed journals and more than 7 book chapters and 8 books. She participated in more than 60 FDP,workshops and webinars. She completed 45 days summer faculty Research Fellowship program at IIT Delhi in the year May 2019.
Multimodal Artificial Intelligence: Foundations, Intelligent Applications, and Emerging Trends presents a comprehensive overview of the fundamental concepts, advanced methodologies, practical applications, and emerging developments in multimodal artificial intelligence. The book explores the integration of diverse data modalities, including text, images, audio, video, and sensor information, to enhance intelligent analysis, prediction, classification, and decision-making. It covers a wide range of applications, including healthcare monitoring, clinical decision support, personalized education, student performance prediction, intelligent transportation, autonomous vehicles, smart agriculture, environmental monitoring, industrial automation, cybersecurity, financial fraud detection, e-commerce recommendation systems, and smart energy management. The volume also examines contemporary technologies such as machine learning, deep learning, computer vision, natural language processing, Transformer architectures, attention mechanisms, generative AI, foundation models, and agentic AI. Furthermore, it addresses important challenges associated with multimodal data integration, privacy, security, computational complexity, explainability, interoperability, and responsible AI implementation. This book serves as a valuable academic reference for researchers, faculty members, postgraduate students, research scholars, and industry professionals interested in developing reliable, scalable, and intelligent multimodal AI solutions across diverse application domains.