Location-based services (LBS) have become more and more important with the development of Artificial Intelligence of Things (AIoT) technology and increasing popularity of IoT terminals in recent years. Global Navigation Satellite System (GNSS) has been widely used for positioning outdoors while it is still challenging to realize autonomous, precise, and universal indoor localization based on the existing mobile devices. Among most indoor positioning technologies, the Wireless Fidelity (Wi-Fi)-based positioning is regarded as an effective way for realizing ubiquitous and high-precision indoor navigation, especially after the presentation of next-generation Wi-Fi access point which supports the state-of-the-art Wi-Fi Fine Time Measurement (FTM) protocol. In addition, with the development of geospatial big data and artificial intelligent (AI), crowdsourced navigation using daily life trajectories data provided by public users become an effective way for autonomously generating Wi-Fi received signal strength indicator (RSSI) database and realizing large-scale indoor localization. This chapter presents an advanced Wi-Fi RSSI-/FTM-integrated indoor positioning technology from the aspects of basic principle, technic route, and real-world experiments and evaluations. We detail the specific procedure of how to realize the crowdsourced Wi-Fi RSSI positioning solution, enhanced Wi-Fi FTM positioning solution, and final intelligent integration model of overall hybrid Wi-Fi positioning system. Moreover, the challenges of indoor positioning are pointed out and the recommendations for future developments of Wi-Fi positioning system are discussed at the end of this chapter.