Technologies that can be used for location outdoors are readily available using Global Positioning Systems (GPS) whilst technologies used for indoor location still prove to be a challenge. Technologies such as Radio Frequency Identification (RFID), Bluetooth, and Wi-Fi, together with location algorithms that include optimization, still require further research for large-scale deployments. This study adopts Bluetooth Low Energy technology and uses the Received Signal strength Indicator (RSSI) from messages as a data source. We then analyse the RSSI from Low Power Nodes, their calculated mean, median and mode values as a basis for further use in an indoor real time location system. Fingerprint databases have been used extensively as a reference to determine location. However, due to the changing indoor environment these may become outdated very quickly. Therefore, this study proposes the use of a Link Quality Indicator as a reference point for further calculation of the location of an asset or a person. The Nordic System on Chip (SOC) is used as the low power node together with a series of Raspberry Pi gateways. Results show that the mean and mode can be used in combination to filter and smooth RSSI values. These calculated RSSI values can then be used and as inputs for an indoor location engine for location determination.