We spend 90% of our time indoors. Buildings became larger and more complex (international airports, subway stations, shopping malls or hospitals for example). Our behaviour has changed. Given the possibilities of ubiquitous technology, we are used to finding out what our position is whenever we want – so far almost exclusively outdoors, however. We have little data on where and how people move indoors. There are various technologies for Indoor Positioning, but none of them dominates the market because of the very different requirements of the large range of applications. With Bluetooth Low Energy (BLE or Bluetooth Smart), a new technology has entered the market, and using it for Indoor Positioning is currently at the forefront of developments. Common positioning methods based on BLE include lateration, angulation, fingerprinting and proximity solutions. Most of them are based on the Received Signal Strength Indicator (RSSI). The RSSI correlates with the distance between transmitter and receiver antenna. However, the link is not as continuous as mathematical models suggest. The RSSI is influenced by many variables, some of which can be controlled and others not. This paper sums up general BLE positioning methods and the challenges they face with RSSI.