Title Development of an Automatic Classification Model for Construction Site Photos with Semantic Analysis based on Korean Construction Specification
Authors Park, Min-Geon ; Kim, Kyung-Hwan
DOI https://dx.doi.org/10.6106/KJCEM.2024.25.3.058
Page pp.58-67
ISSN 2005-6095
Keywords Deep Learning; Image Classification; Data Management; Construction Specification
Abstract In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.