Περίληψη: | The aim of this study is the development and implementation of an advanced human
and IoT interaction platform based on Wireless Sensor Networks and Embedded IMU
Systems. The aforementioned application is able to recognize hand gestures and depending
on the characteristics of those, perform specific actions in an Ambient Assisted Living
Environment. This provides a service for people incapable of self-sufficiency in their place
of living, in a non invasive way. This topic has recently been receiving a lot of attention
because it provides support to patients and elderly people like no other domain and is of
a great technological interest.
During the development of this study we have used a single IMU sensor that transmits
its data with the use of BLE (Bluetooth Low Energy) technology and by taking advantage
of the MQTT, IoT communication protocol, we establish a fully remote and autonomous
application. By using the Python programming language and implementing Madgwick’s
filter for Quaternion-based rotational representation of our object, we have managed to
establish a really accurate and instantaneous three dimensional performance. Furthermore
we exploit the domain of Neural Networks and its various classification techniques while
decisively applying a Multilayer Perceptron to effectively recognize the specified gestures.
This thesis provides a detailed analysis of related scientific areas and aims to provide
the reader with the tools to fully comprehend the suggested solution. During this process
we have found that it is possible to use a low-power, low-cost sensor to develop a state-ofthe-art, accurate result. We also managed to combat overfitting problems while creating
our own dataset and engaging in data augmentation techniques. Finally, we were able to
create a platform that classifies between gestures in real time and provides the foundations
to act upon them.
We believe that this application can be the foundations for similar ones in the future
and aid in the development of more complex Internet of Things and Assisted Living
platforms.
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