Arquitetura para gerenciamento de dispositivos através de assistentes virtuais comandados por voz
The number of IoT devices in the world grows exponentially and is expected to exceed 75 billion in the coming years. Its use in home automation processes has grown and, as a result, an increasing number of users without technical knowledge (or with reduced technical knowledge) have made use of thes...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/47637 |
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| Resumo: | The number of IoT devices in the world grows exponentially and is expected to exceed 75
billion in the coming years. Its use in home automation processes has grown and, as a result, an increasing number of users without technical knowledge (or with reduced technical knowledge) have made use of these devices. The wide variety of manufacturers and the
lack of standardization in the features available can generate doubts among users and lead
them to make wrong settings, harming the management of these equipments. Performing
these settings can be even more challenging for people with disabilities. According to
data presented by IBGE, more than 45 million people have some type of disability, which
corresponds to almost 24% of the population. Faced with these challenges, this work proposes a layered architecture, based on independent modules, where this architecture will
allow, through voice commands or text and using natural language, a user can perform
complex configurations, without the need for advanced technical knowledge regarding
infrastructure or specifics of the network device used. For this purpose, among other technologies, natural language processing, machine learning and text-to-speech conversion
will be used. A survey of the state of the art regarding solutions aimed at configuring,
activating and monitoring devices is presented, as well as a prototype for validation and
evaluation of the functioning of the architecture proposed in this research. Future improvements can be implemented in the chatbot, its design was submitted to an evaluation to
identify possible existing problems. Finally, in the quantitative tests carried out to verify
the assertiveness of the prototype developed, its accuracy was greater than 83%. |
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