Digital Documentation, Photogrammetry, Artificial intelligence, Algorithm
Architecture | Artificial Intelligence and Robotics | Arts and Humanities | Data Science | Engineering | Theory and Algorithms
Natural and human-made disasters have significant impacts on monumental buildings, threatening them from being deteriorated. If no rapid consolidations took into consideration traumatic accidents would endanger the existence of precious sites. In this context, Beirut's enormous 4th of August 2020 explosion damaged an estimated 640 historical monuments, many volunteers assess damages for more than a year to prevent the more crucial risk of demolitions. This research aims to assist the collaboration ability among photogrammetry science, Artificial Intelligence Model (AIM) and Architectural Coding to optimize the process for better coverage and scientific approach of data specific to the crack disorders to build a comprehensive model consolidation technique. Despite the current technological improvement, the restoration of the existing monument is a challenging and lengthy process where the actual site situation's re-ignitions consume enormous time, from assessing the damages to establishing the restoration relying on human resource developments and manual drawings.
Author ORCID Identifier
Said Maroun - https://orcid.org/ 0000-0002-3124-3158
Mostafa Khalifa - https://orcid.org/ 0000-0001-5306-839X
Nabil Mohareb - https://orcid.org/ 0000-0001-9036-0381
Maroun, Said; Khalifa, Mostafa; and Mohareb, Nabil
"ASSESSING PHOTOGRAMMETRY ARTIFICIAL INTELLIGENCE IN MONUMENTAL BUILDINGS’ CRACK DIGITAL DETECTION,"
Architecture and Planning Journal (APJ): Vol. 28:
1, Article 9.
Available at: https://digitalcommons.bau.edu.lb/apj/vol28/iss1/9