This licentiate thesis proposes a digitalization framework that integrates Internet of Things (IoT), cloud computing, ontology, and machine learning to address the challenges of smart maintenance of historic buildings. IoT devices enable data collection from historic buildings to reveal their latest status, while a public cloud platform provides stable and scalable resources for storing data, performing analytics, and deploying applications. Ontologies provide a clear and concise way to organize and represent building data, and combined with IoT devices and ontologies, parametric digital twins can be created to evolve with their physical counterparts. Machine learning can be used to identify patterns from data and provide decision-makers with insights to achieve smart maintenance.
Related Posts
