IHBC Yearbook 2022

42 Y E A R B O O K 2 0 2 2 when saturated is particularly relevant given climate change, with fabric being wetter for longer. Early, accurate detection and monitoring of such issues are important to reduce deterioration. Classical surveying protocols require the systematic consideration of manifestation, identification and diagnosis of defects, with subsequent treatment (repair selection and fabric intervention), through to longer term monitoring of performance. The evaluation of each of these stages are well established and fundamental to holistic maintenance, repair and building operation. These activities have the potential to benefit greatly from progressive digital technologies that better support survey operations and assessment of longer-term fabric performance. By comparison, traditional visual survey of buildings has been shown to be subjective and can yield results that vary greatly from one evaluator to another. Each stage of survey intervention has the potential for greater divergence in reporting and this has significant implication for establishing an objective starting point for successive intervention. In essence, two surveyors confronted with the same building could attribute quite different diagnosis, prognosis and therapy (fabric intervention). While one might take a minimal intervention (or do nothing) approach, the other might suggest greater, often unnecessary levels of intervention. The implications of overzealous intervention would be greater financial and carbon cost, and risks unnecessary loss of culturally significant historic fabric. Creating objectivity in a survey is clearly fundamental to all resulting operations and practices. Over the last two decades digital reality capture has gradually become ubiquitous in its application for recording, documentation and interpretation of buildings; acquisition of data is relatively cheap and fast to attain but the realisation of sector transformation and true digital disruption in working practices has yet to be achieved widely. In essence, capturing digital data has become easy, but meaningfully extracting value from digital data is what is important, offering the promise of better supported conservation and maintenance that is economically, environmentally, technically and philosophically enhanced. However, this remains challenging. SURVEY ANALYSIS BY ALGORITHMS The deployment of progressive digital reality technologies that go beyond digital documentation processes have been shown to enhance levels of objectivity in survey and reporting and facilitate more effective, targeted intervention. For example, we (Enrique Valero, Frédéric Bosché and Alan Forster) in partnership with Historic Environment Scotland (HES) have developed digital applications for the survey, repair, and maintenance of historic buildings in our Historic Digital Survey (HDS) Project series. The projects have broadly evaluated the efficacy of digital reality capture technologies and developed bespoke algorithms for the extraction of value from point cloud data, such as automatic segmentation of rubble and ashlar masonry. These opensource algorithms have been published as a plugin to the free software CloudCompare. As part of the automatic segmentation process, the open- source algorithm can be applied to calculate the number of stones, the linear meterage of mortar and, importantly within the context of repair intervention, direct the surveyor to those regions of mortar that are significantly recessed and therefore likely to require repair. When applied to mortar joints these automatic depth maps provide a rapid, overt visual indicator of where intervention may be necessary (see fig 1). An algorithm has also been developed for the segmentation of individual stones in ashlar masonry which is of particular importance in replacement of dimensional stone. These technologies objectify the survey process and can reduce the likelihood of unnecessary works. While still under development and validation, the algorithms are firmly focused on enhancing productivity in building conservation, saving both time and money but also Fig 1: Successive application of digital tools – a) point cloud; b) automatic segmentation; c) identification of mortar joint regions; d) depth map of recessed mortar regions a b c d