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Sistema IoT de monitorização da qualidade ambiental e postural
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A presente dissertação apresenta o desenvolvimento de um sistema baseado na Internet
das Coisas para monitorizar a qualidade ambiental e postural em salas de aula, com o objetivo
de promover o bem-estar e o desempenho académico dos estudantes. Foram desenvolvidos
sensores especializados para medir parâmetros como temperatura, dióxido de carbono,
partículas suspensas, ruído, iluminação e postura. O sistema integra cadeiras inteligentes
equipadas com sensores e algoritmos de inteligência artificial para avaliar posturas e sinais vitais,
bem como uma rede integrada para centralizar os dados num dashboard interativo. A
metodologia incluiu o design e validação de protótipos, com testes em diferentes condições e
análise dos resultados através de métricas de precisão e eficiência. Os principais resultados
destacam a eficácia do sistema na monitorização contínua de parâmetros ambientais e posturais,
permitindo ajustes em tempo real e contribuindo para a criação de ambientes de aprendizagem
mais saudáveis e eficientes. Este trabalho apresenta um impacto positivo não só no contexto
educacional, mas também em outros cenários, como hospitais e escritórios, demonstrando a
versatilidade da solução proposta.
This dissertation presents the development of a system based on the Internet of Things to monitor environmental and postural quality in classrooms, aiming to promote students’ well-being and academic performance. Specialized sensors were developed to measure parameters such as temperature, carbon dioxide, particulate matter, noise, lighting, and posture. The system integrates smart chairs equipped with sensors and artificial intelligence algorithms to evaluate postures and vital signs, as well as a networked system that centralizes data in an interactive dashboard. The methodology included the design and validation of prototypes, testing under different conditions, and analysis of results using metrics for precision and efficiency. The main findings highlight the system’s effectiveness in continuously monitoring environmental and postural parameters, enabling real-time adjustments and contributing to healthier and more efficient learning environments. This work demonstrates a positive impact not only in educational contexts but also in other scenarios, such as hospitals and offices, showcasing the versatility of the proposed solution.
This dissertation presents the development of a system based on the Internet of Things to monitor environmental and postural quality in classrooms, aiming to promote students’ well-being and academic performance. Specialized sensors were developed to measure parameters such as temperature, carbon dioxide, particulate matter, noise, lighting, and posture. The system integrates smart chairs equipped with sensors and artificial intelligence algorithms to evaluate postures and vital signs, as well as a networked system that centralizes data in an interactive dashboard. The methodology included the design and validation of prototypes, testing under different conditions, and analysis of results using metrics for precision and efficiency. The main findings highlight the system’s effectiveness in continuously monitoring environmental and postural parameters, enabling real-time adjustments and contributing to healthier and more efficient learning environments. This work demonstrates a positive impact not only in educational contexts but also in other scenarios, such as hospitals and offices, showcasing the versatility of the proposed solution.
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Palavras-chave
IoT Qualidade do Ar Postura Cadeiras inteligentes Inteligência Artificial Aprendizagem Internet of Things Air Quality Posture Smart Chairs Artificial Intelligence Learning