Through the combination of virtual and real, multi-dimensional perception, and accurate
map**, digital twin (DT) could describe the physical world in real-time and provide a …

Buildings have been consistently identified as the sector with the greatest potential to reduce
both energy consumption and carbon dioxide (CO 2) emissions through more sustainable …

Nowadays, unmanned aerial vehicles (UAVs) are frequently used for periodic visual
inspection of building envelopes to detect unsafe conditions or vulnerable damages …

Develo** a classifier to identify the defects from façade images using deep learning
requires abundant labeled images. However, it is time‐consuming and uneconomical to …

End users' maintenance requests gathered from computerized maintenance management
systems (CMMS) configure a rich source of information to evaluate the occupants' …

Usually, maintenance models consider maintenance actions as perfect, ie these
interventions can restore the components to the “as good as new” state. However, in many …

The technical performance assessment of a building is essential for planning maintenance
actions to improve its condition and functionality. The aim of this study is to present a …

Façade defect classification based on deep learning has made great progresses in recent
years. However, deep learning models commonly need abundant labeled data for training …

Visual evaluation of façade condition plays an important role to ensure the structural health
of the whole building. To automatically achieve visual evaluation of façade condition with …

The importance of knowing the service life of buildings and their components is recognized.
Several studies have been developed, in different countries, to address this research topic …