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Dr. M. Ananthi is a Professor in the Department of Computer Science and Engineering at KGISL Institute of Technology, Coimbatore, Tamil Nadu, India. She has extensive academic experience in computer science education and research. Her research interests include Artificial Intelligence, Machine Learning, predictive analytics, data science, cloud computing, and intelligent information systems. She actively contributes to research, mentoring, and curriculum development in emerging computing technologies.
Artificial Intelligence (AI) has emerged as a revolutionary tool for predictive analytics, facilitating astute decision-making in diverse intelligent systems such as healthcare, transportation, agriculture, manufacturing, finance, education, smart cities, and industrial automation. The amalgamation of artificial intelligence with the Internet of Things (IoT), cloud computing, edge computing, and Big Data Analytics has markedly augmented organisations' capacity to forecast future occurrences, optimise resource allocation, diminish operational expenses, and bolster system dependability. Predictive analytics employs both historical and real-time data to anticipate results, recognise patterns, uncover irregularities, and facilitate proactive decision-making. Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), and Explainable Artificial Intelligence (XAI) enhance predictive abilities by autonomously discerning intricate patterns from extensive datasets. This chapter delineates the fundamentals, structure, artificial intelligence methodologies, applications, obstacles, and prospective research avenues of predictive analytics in intelligent systems.