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Desenvolvimento de um sistema didático baseado em Raspberry PI para o ensino da domótica
| Name: | Description: | Size: | Format: | |
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| 5.29 MB | Adobe PDF |
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Abstract(s)
A presente dissertação tem por objetivo o desenvolvimento de um sistema didático baseado em tecnologia IoT, utilizando a plataforma Raspberry Pi para apoio ao ensino da domótica em contextos de formação técnica e superior. O protótipo concebido integra sensores de temperatura e humidade (DHT22), luminosidade (LDR) e movimento (PIR), bem como atuadores destinados ao controlo de iluminação e estores, possibilitando a simulação de ambientes inteligentes A arquitetura proposta assenta numa abordagem modular e de baixo custo, recorrendo a programação em Python, comunicação via GPIO e interface web desenvolvida em Flask. Esta combinação permite aos utilizadores monitorizar condições ambientais e interagir com os dispositivos em tempo real, assegurando simultaneamente funcionalidades de automatização, supervisão remota e envio de notificações. O protótipo concebido constitui um recurso educativo capaz de apoiar metodologias de aprendizagem ativa, nomeadamente a aprendizagem baseada em projetos, promovendo a aquisição de competências nucleares na domótica e nas tecnologias digitais aplicadas a edifícios inteligentes. A dissertação, por sua vez, delineia propostas de melhoria e perspetivas de trabalho futuro orientadas para o alargamento das funcionalidades do sistema e para o reforço da sua maturidade técnica e valor formativo.
This dissertation presents the development of an educational system based on IoT technologies using the Raspberry Pi platform to support the teaching of home automation in technical and higher education contexts. The proposed prototype integrates temperature and humidity sensors (DHT22), a light sensor (LDR), and a motion sensor (PIR), along with actuators for lighting and shutter control, enabling the simulation of smart home environments. The system architecture follows a modular and low-cost approach, employing Python programming, GPIO-based communication, and a web interface developed using Flask. This setup allows users to monitor environmental conditions and interact with devices in real time, providing automation features, remote supervision, and automatic alerts. The developed prototype constitutes an effective educational tool that supports active, project-based learning methodologies, fostering essential competencies in home automation and digital technologies applied to smart buildings. The dissertation also outlines improvement recommendations and future work directions aimed at expanding the platform and incorporating additional functionalities, further enhancing its educational value.
This dissertation presents the development of an educational system based on IoT technologies using the Raspberry Pi platform to support the teaching of home automation in technical and higher education contexts. The proposed prototype integrates temperature and humidity sensors (DHT22), a light sensor (LDR), and a motion sensor (PIR), along with actuators for lighting and shutter control, enabling the simulation of smart home environments. The system architecture follows a modular and low-cost approach, employing Python programming, GPIO-based communication, and a web interface developed using Flask. This setup allows users to monitor environmental conditions and interact with devices in real time, providing automation features, remote supervision, and automatic alerts. The developed prototype constitutes an effective educational tool that supports active, project-based learning methodologies, fostering essential competencies in home automation and digital technologies applied to smart buildings. The dissertation also outlines improvement recommendations and future work directions aimed at expanding the platform and incorporating additional functionalities, further enhancing its educational value.
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Keywords
Domótica IoT Raspberry Pi Casas Inteligentes Plataforma Educativa Home Automation Smart Homes Educational Systems