Automating Defect Detection for the Preservation of Historical Structures

Preserving cultural heritage sites is important for safeguarding their historical value and ensuring public safety. These sites are endangered by natural aging processes, environmental conditions (like climate change), and human activites. Traditional inspection methods are slow, labour- intensive and subject to substantial error. Existing works identify defects such as cracks, spalling, exposed bricks, and discoloration but does not cover vegetation and no segmentation as well. This paper proposes an automated defect detection system by using CNN based models along with Canny edge detector algorithm which provides a visual aid in localizing edges for heritage site preservation . The automated defect detection system can be used to monitor the condition of structures in real time, which leads to early detection of cracks and discoloration and will prevent greater loss . It is a scalable solution that optimizes overall efficiency and accuracy for heritage preservation, enabling proactive maintenance to guarantee the ongoing protection of invaluable cultural sites. When combined with live feeds from CCTV or drone cameras, the system could precisely identify and segment defects, allowing for faster corrective actions and minimizing manual inspections.