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Abstract: Indoor positioning is a critical technology with a broad spectrum of applications spanning from navigation systems in smart buildings to asset tracking in industrial environments. This research paper explores the effectiveness of four prominent techniques in indoor positioning: Euclidean Distance, Trilateration, Wi-Fi Round Trip Time (RTT), and the Fast Time Measurement (FTM) Protocol. In this study, we conducted extensive experiments and analysis to evaluate the accuracy and performance of these methods within diverse indoor settings. Our findings reveal that Euclidean Distance, when coupled with fingerprinting techniques, achieved an average positioning accuracy of ±1.5 meters in a real-world indoor environment. Trilateration, leveraging signals from strategically placed beacons, demonstrated even greater precision with an average accuracy of ±0.5 meters. Moreover, Wi-Fi RTT emerged as a promising approach, delivering an accuracy of ±0.3 meters in test scenarios. Furthermore, statistical analysis revealed that these techniques perform consistently across different indoor environments, regardless of factors such as signal obstructions and variations in signal strength. These results underscore the versatility and reliability of these indoor positioning methods, making them viable options for a wide range of applications. In conclusion, this research not only provides valuable insights into the capabilities of Euclidean Distance, Trilateration, Wi-Fi RTT, and FTM Protocol but also underscores their potential to transform indoor positioning accuracy. These findings pave the way for improved indoor navigation, asset tracking, and location-based services, with significant implications for industries such as logistics, healthcare, and smart building management.