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A Framework for Profiling based on Music and Physiological State
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Orientador(es)
Resumo(s)
The IoT (Internet of Things) is an emergent technological area with distinct chal-lenges, which has been addressed by the world research community. This disser-tation proposes the use of a knowledge-based framework capable of supporting the representation and handling of devices along with some autonomous inter-action with the human being, for creating added value and opportunities in IoT. With usability in mind, the objective lays in an attempt to characterize users’ physiological status mainly through music in a profiling approach. The idea is to produce a solution able to customize the environment by musical suggestions to the actual scenarios or mood that the users lie in. Such system can be trained to understand different physiological data to then infer musical suggestions to the users. One of the adopted methods in this work explores that thought, on whether the usage of a person’s physiological state can wield adequate sensorial stimulation to be usefully used thereafter. Another question considered in this work is whether it is possible to use such collected data to build user’s musical playlists and profile that tries to use the user’s physiological state to predict his or her emotional state with the objective to reach a well-being situation.
Descrição
Palavras-chave
Data analysis Musical recommendation Ontologies Knowledge representation Physiological states