Indoor localization addresses the limitations of GPS in enclosed environments, where signal obstructions and complex spatial configurations hinder traditional positioning systems. Chapter 1 introduces intelligent indoor localization, highlighting its unique challenges and opportunities. It explores the differences between indoor and outdoor positioning, focusing on solutions to improve accuracy, adaptability, and intelligence. The chapter also highlights advanced technologies like machine learning and outlines the book’s focus on three key areas: efficientChannel State Information (CSI)Channel State Information (CSI) collection, intelligent CSI updates, and accurate localization. These themes aim to reduce manual effort, enhance real-time adaptability, and improve accuracy for impactful applications. The chapter also emphasizes the significance of CSI in wireless communications, demonstrating its ability to capture detailed signal properties beyond other localization signals. Comparing traditional techniques such as trilateration, triangulation, and fingerprinting, underscores CSI’s advantages in addressing complex indoor scenarios. By providing a cohesive understanding of CSI’s role, this chapter establishes a foundation for the development of robust, intelligent localization systems and serves as a roadmap for exploring the challenges and innovations presented throughout the book.