This thesis compares and evaluates the accuracy of two RSSI-based tri-lateration methods in an indoor setting, implementing either Wi-Fi andBluetooth Low Energy (BLE) while using commercially available hardware.The purpose of evaluation is part of the long-term vision of improving thesafety of workers in adverse environments such as factories, by providing awearable Indoor Positioning System where other systems like GPS are notsuitable due to signal obstruction. Within a confined space replicating in-tended real-world conditions in terms of signal attenuation and adversity,30 consecutive measurements of signal strength readings (RSSI) to threereference nodes were collected at 10 randomized sample positions, andwas repeated across 5 tests. The accuracy of trilateration was evaluatedusing an averaged Root Mean Square Error (RMSE) over the five tests. Itwas observed that RSSI using Wi-Fi achieved better accuracy of predictingthe actual position within the testing environment than signal-strength us-ing BLE, with Wi-Fi and BLE achieving an accuracy of 0.88 and 1.85 metersrespectively. However, because of the power efficiency of BLE it is a viablecandidate for a future low-cost and device-based Indoor Localization Sys-tem to potentially be used and worn by workers. The results while alignedwith similar existing literature, infer what a low-cost indoor positioningsystem might achieve. Future research with the goal of developing suchsolutions could benefit from implementing both Wi-Fi and BLE as the basisof signal strength trilateration.