Zpracování dat ze senzorů wearable zařízení pomocí strojového učení

The goal of this master's thesis is to analyze the situation of wearable devices with the Android Wear operating system and recognition capabilities of various movement activities using neural networks. The primary focus is therefore on identifying and describing the most appropriate tool for recognizing dynamic movements using machine learning methods based on data obtained from this type of devices. The practical part of the thesis then comments on the implementation of a stand-alone Android Wear application capable of recording and formatting data from sensors, training the neural network in a designed external desktop tool, and then reusing trained neural network for motion recognition directly on the device.

wearables, smart devices, smart watches, android wear, neural network, tensorflow, activity recognition, accelerometer, python, convolutional neural networks, machine learning, movement detection