This paper presents a comprehensive evaluation of the LIPTracker System in a classroom context. LIPTracker is an innovative human presence tracking system designed for indoor environments. Leveraging devices connected to a shared access point and through the analysis of the RSSI signal strength, LIPTracker detects the presence of students and monitors their real-time location in the classroom. The Triangulation with proximity detection to the exit point was the method used in this version of the LIPTracker system, which consists of detecting devices near the exit using three access points as references. These access points are located at known positions in the area of interest. Through data collected in authentic classroom environments, the paper evaluates the accuracy of LIPTracker. Applying the Kalman filter helped to improve localization accuracy and to reduce distorted signals, resulting in a detection rate of approximately 95%. Additionally, insights into technical challenges and potential improvements are discussed.