Title A Developing a Machine Leaning-Based Defect Data Management System For Multi-Family Housing Unit
Authors Park, Da-seul ; Cha, Hee-sung
DOI https://dx.doi.org/10.6106/KJCEM.2023.24.5.035
Page pp.35-43
ISSN 2005-6095
Keywords Apartment Buildings; Defect Management; Machine Learning; OCR; Generative Information Extraction
Abstract Along with the increase in Multi-unit housing defect disputes, the importance of defect management is also increased. However, previous studies have mostly focused on the Multi-unit housing’s 'common part'. In addition, there is a lack of research on the system for the 'management office', which is a part of the subject of defect management. These resulted in the lack of defect management capability of the management office and the deterioration of management quality. Therefore, this paper proposes a machine learning-based defect data management system for management offices. The goal is to solve the inconvenience of management by using Optical Character Recognition (OCR) and Natural Language Processing (NLP) modules. This system converts handwritten defect information into online text via OCR. By using the language model, the defect information is regenerated along with the form specified by the user. Eventually, the generated text is stored in a database and statistical analysis is performed. Through this chain of system, management office is expected to improve its defect management capabilities and support decision-making.