Bluetooth Low Energy (BLE) is a wireless technology for exchanging data, over short distances, designed for the Internet-of-Things era. As widely supported by wearable devices, BLE has the potential to become an alternative for indoor-localization and proximity sensing. The aim of this work was to perform a thorough characterization of the RSSI-distance relationship under controlled conditions using two BLE devices. Four calibration models underwent to a comparative evaluation analysis. The best results were obtained using a polynomial model with a mean distance percentage error equal to 25.7% (0.4 m) in the range 0-3 m. An overall improvement of 14.3% (0.24 m) in the distance estimate compared to the exponential model commonly adopted in the literature was reported

This work presents a novel wireless and low power Attitude and Heading Reference Systems network based on lowcost MEMS (Micro Electro-Mechanical System) sensors, developed for motion tracking systems. Biomedical and rehabilitation purposes as well as gaming and consumer electronics may be the potential applications of this network. The paper aims to describe the hardware architecture, the embedded sensor fusion algorithm and the motion tracking system.

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