Towards an automatized and objective assessment of data from visual inspections of building envelopes
Paper in proceeding, 2022
The renovation planning process is filled with uncertainties and subjective decisions. These make the decisions upon what and when to renovate a complex and ambiguous problem. Selection of renovation measures related to building envelope are often far from optimal as decisions are usually made based on visual inspections. These are manned and thus prone to subjective assessment and the knowhow of individual inspectors. Furthermore, objective criteria which could indicate non-structural failures are often missing. The objective based planning process allowing the estimation of the current damage status of the building envelope by only using non-destructive measurements is still in its infancy. The first step requires establishing reliable and objective based data collection. These could be efficiently collected by Unmanned Aerial Vehicles (UAV) with subsequent image recognition algorithms allowing the identification of imperfections and store the position and extent of such deviations into the building’s digital assessment database. Such tools do not exist. The aim of this study is to investigate the current objectivization possibilities in the domain of building inspections. The first part provides a literature review describing how an autonomous UAV survey of a building envelope may be planned and what computer vision techniques may be used for automatic damage recognition and classification. Subsequently, an objective detection model based on the YOLO-tiny (You Only Look Once) computer vision framework is employed in a case study investigating a building envelope of historical Tjolöholm castle in Sweden. This study contributes to developing a methodology for an objective based visual inspection process.