This study covers the setup and analysis of software designed to use personal mobile devices for localised occupancy detection. The need to detect occupants more accurately has been identified as an important route to designing building controls that cater building energy usage directly to occupant needs, potentially saving wasted energy and improving occupant comfort. However, localised occupant data can be difficult to obtain with accuracy and typically relies on environmental sensors such as CO2 and motion detectors, which do not allow for individual occupants to be identified. In this study, software for devices using the Android operating system was developed to detect the presence of Bluetooth beacons. The software was designed to operate in a building with one beacon in each monitored zone. Where multiple beacons are detected, the software set up logic to select the appropriate zone. The software was then tested on a single device in two settings: a simplified setting over a single floor, with three monitored zones and two occupants, and a small office setting with nine monitored zones and 10-15 regular occupants. The results showed that the software was able to correctly detect the occupant’s location with high accuracy in the simplified setting. However, when applied to the more complex setting, it was found that the wrong zone was identified for a majority of the time during some tests. The reasons for this change in performance were tested and identified: the interference in Bluetooth signal strength caused by the human body had a greater effect than the decrease in strength caused by building material, meaning that a large number of people moving in the building can affect the signal received by a static device.