Accurate Indoor Proximity Zone Detection Based on Time Window and Frequency with Bluetooth Low Energy

The information of user's proximity to micro-location in an indoor space allow us to infer the user's interest and intention. With help of this information, it is possible to realize important real world tasks, for instance, context aware service, automation of common tasks and so on. Recently, there have been many studies on the indoor proximity detection with BLE(Bluetooth Low Energy) and various techniques such as filtering and curve fitting have been suggested for the improvement of accuracy. However, those techniques are not adequate for the accurate indoor proximity detection, which limit the usable space and increase the error detection rate. In this study, we proposed the accurate indoor proximity zone detection technique based on time window, frequency of RSSI(Received Signal Strength Indicator) and user's walking.