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Otimização tecnológica para a gestão inteligente dos recursos energéticos numa unidade hoteleira no Algarve
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Orientador(es)
Resumo(s)
A eficiência energética e a sustentabilidade são hoje fatores críticos para o setor do turismo, exigindo soluções inovadoras que conciliem conforto, competitividade e responsabilidade ambiental. Neste contexto, a presente dissertação centra-se na gestão de energia, na monitorização contínua e na otimização de recursos energéticos numa unidade hoteleira de grande dimensão no Algarve, tendo como tema central a aplicação dos conceitos da indústria 4.0 e da inteligência artificial para promover eficiências energética e hídrica e apoiar a manutenção preditiva. O estudo analisa três anos de dados de eletricidade, água e gás, correlacionados com variáveis operacionais como ocupação e sazonalidade, aplicando modelos inteligentes para prever consumos, identificar anomalias e quantificar desvios operacionais. A integração da indústria 4.0 com algoritmos de inteligência artificial revela-se decisiva para transformar grandes volumes de dados em informação estratégica, permitindo não apenas antecipar falhas e otimizar ciclos de manutenção, mas também reduzir de forma consistente a pegada carbónica associada às operações hoteleiras. A monitorização contínua dos consumos de eletricidade, água e gás, quando aliada a modelos preditivos, possibilita identificar padrões de desperdício e implementar medidas corretivas em tempo real, assegurando que os recursos são utilizados de forma mais eficiente. Neste contexto, os gráficos de controlo assumem um papel central como ferramentas de apoio à decisão, uma vez que permitem visualizar desvios face ao comportamento esperado, quantificar o erro relativo diário e estabelecer limites de alerta para consumos anómalos. A utilização destas ferramentas não
só reforça a capacidade de diagnóstico operacional, como também contribui para a definição de estratégias de mitigação alinhadas com os objetivos de neutralidade carbónica. Assim, a aplicação integrada destas metodologias transforma o hotel numa infraestrutura inteligente e resiliente, capaz de responder dinamicamente às exigências de sustentabilidade, eficiência e rentabilidade, ao mesmo tempo que se posiciona como referência no setor turístico pela sua gestão responsável dos recursos energéticos e ambientais.
Energy efficiency and sustainability are today critical factors for the tourism sector, demanding innovative solutions that reconcile comfort, competitiveness, and environmental responsibility. In this context, this dissertation focuses on energy management, continuous monitoring, and the optimization of energy and water resources in a large hotel unit in the Algarve, with its central theme being the application of Industry 4.0 concepts and Artificial Intelligence (AI) to promote both energy and water efficiency while supporting predictive maintenance. The study analyzes three years of electricity, water, and gas consumption data, correlated with operational variables such as occupancy and seasonality, applying intelligent models to forecast consumption, detect anomalies, and quantify operational deviations. The integration of Industry 4.0 with AI algorithms proves decisive in transforming large volumes of data into strategic information, enabling not only the anticipation of failures and the optimization of maintenance cycles but also the consistent reduction of the carbon footprint associated with hotel operations. Continuous monitoring of electricity, water, and gas consumption, when combined with predictive models, makes it possible to identify waste patterns and implement corrective measures in real time, ensuring more efficient use of resources. In this context, control charts emerge as central decision-support tools, as they allow the visualization of deviations from expected behavior, the quantification of daily relative error, and the establishment of alert thresholds for anomalous consumption. The use of these tools not only strengthens operational diagnostic capacity but also contributes to the definition of mitigation strategies aligned with carbon neutrality goals. Ultimately, the integrated application of these methodologies transforms the hotel into an intelligent and resilient infrastructure, capable of dynamically responding to the demands of sustainability, efficiency, and profitability, while positioning itself as a reference in the tourism sector through the responsible management of energy and environmental resources.
Energy efficiency and sustainability are today critical factors for the tourism sector, demanding innovative solutions that reconcile comfort, competitiveness, and environmental responsibility. In this context, this dissertation focuses on energy management, continuous monitoring, and the optimization of energy and water resources in a large hotel unit in the Algarve, with its central theme being the application of Industry 4.0 concepts and Artificial Intelligence (AI) to promote both energy and water efficiency while supporting predictive maintenance. The study analyzes three years of electricity, water, and gas consumption data, correlated with operational variables such as occupancy and seasonality, applying intelligent models to forecast consumption, detect anomalies, and quantify operational deviations. The integration of Industry 4.0 with AI algorithms proves decisive in transforming large volumes of data into strategic information, enabling not only the anticipation of failures and the optimization of maintenance cycles but also the consistent reduction of the carbon footprint associated with hotel operations. Continuous monitoring of electricity, water, and gas consumption, when combined with predictive models, makes it possible to identify waste patterns and implement corrective measures in real time, ensuring more efficient use of resources. In this context, control charts emerge as central decision-support tools, as they allow the visualization of deviations from expected behavior, the quantification of daily relative error, and the establishment of alert thresholds for anomalous consumption. The use of these tools not only strengthens operational diagnostic capacity but also contributes to the definition of mitigation strategies aligned with carbon neutrality goals. Ultimately, the integrated application of these methodologies transforms the hotel into an intelligent and resilient infrastructure, capable of dynamically responding to the demands of sustainability, efficiency, and profitability, while positioning itself as a reference in the tourism sector through the responsible management of energy and environmental resources.
Descrição
Palavras-chave
Gestão de energia Monitorização Otimização de recursos energéticos Indústria 4.0 Manutenção preditiva Eficiências energética e hídrica