Throughput Analysis of BLE Sensor Network for Motion Tracking of Human Movements

In the world of smart cities, domotics, wearable sensors, and smart devices, an important role is played by the communication technology involved in the data transmission between nodes of the sensor network. Among a wide set of standard wireless technologies already available on the market, Bluetooth low energy (BLE) is becoming one of the most widespread and exploited. The aim of this paper is to propose a methodology for analyzing and characterizing throughput performance in general sensor network applications. In particular, we want to assess the effective BLE performance in order to investigate its possible usage in applications that require high throughput, such as body area network (BAN) for motion tracking of human movements, using magneto-inertial sensor units (M-IMUs). In addition to this, we have also studied how different nodes, with different hardware, software, and firmware, can affect the network performance. The results of this paper show how different typologies of nodes can be better exploited dependently on the specific application they are involved in. In fact, we define how to set up BLE parameters in order to push this technology to its limit. Finally, we address the specific case of using BLE as the wireless infrastructure of a BAN for human motion tracking: in this scenario, we show that BLE can be employed to successfully transmit M-IMU data from 5 peripheral nodes with a sampling frequency higher than 200 Hz.