Prof.D. Keivan Navaie2026-06-012026-06-01https://dspace.academy.edu.ly/handle/123456789/2116Positioning and navigation services have become increasingly important in our daily lives. Currently, the accessibility and affordability of Global Navigation Satellite System (GNSS) technology for outdoor positioning and navigation are at their peak. The GNSS services, such as Global Positioning System (GPS) technology, used in smartphones, provide an accurate position within approximately 4.9 metres with 95% probability in outdoor environments [3]. However, in indoor environments, GPS cannot function properly due to obstacles that block GPS Radio Frequency (RF) signals from penetrating walls and objects inside buildings.This thesis investigates the design and implementation of Wi-Fi fingerprintingbased Indoor Positioning Systems (IPS), with a focus on enhancing their efficiency, scalability, and accuracy. Wi-Fi fingerprinting, particularly utilising Received Signal Strength Indicator (RSSI) data, offers a cost-effective and non-intrusive method for indoor positioning. Despite its advantages, existing systems encounter challenges such as high computational complexity, the need for frequent manual updates, and difficulties in managing large datasets.On the Efficient Design of Scalable