Abstract
The demand for categorising technology that requires minimum manpower and equipment is increasing because a large amount of waste is produced during the demolition and remodelling of a structure. Considering the latest trend, applying an artificial intelligence (AI) model for automatic categorisation is the most efficient method. However, it is difficult to apply this technology because research has only focused on general domestic waste. Thus, in this study, we delineate the process for developing an AI model that differentiates between various types of construction waste. Particularly, solutions for solving difficulties in collecting learning data, which is common in AI research in special fields, were also considered. To quantitatively increase the amount of learning data, the Fréchet Inception Distance method was used to increase the amount of learning data by two to three times through augmentation to an appropriate level, thus checking the improvement in the performance of the AI model.
Highlights
The construction industry is a pivotal player in the national economy in terms of gross domestic production and employment
This process is in line with the guidebook on establishing a dataset for artificial intelligence (AI) learning published by the National Information Society Agency, an affiliated organisation of Ministry of Science and ICT (Information and Communication Technology) of South Korea, and made quality evaluation on datasets mandatory, unlike the existing research methods [44,45]
The proposed model seems insusceptible to changes in brightness, but is affected by noise or blur; the results can be utilised in data acquisition for developing the model to recognise construction waste
Summary
The construction industry is a pivotal player in the national economy in terms of gross domestic production and employment. According to the World Bank statistics [1], the construction industry is responsible for approximately 24.7% of the gross domestic product on average globally. The construction industry in the South Korean economy plays a key role, accounting for approximately 26.8% of the gross domestic production in 2019 [2]. It is indicated that the construction industry provided approximately two million jobs, accounting for approximately 7.5% of the overall employment in all manufacturing sectors in South Korea [2]. According to the Intergovernmental Panel on the Climate Change report, the construction industry consumes approximately 40% of the total global energy and accounts for approximately 30% of the overall GHG emissions per annum [3]. The generation of construction and demolition waste would cause several environmental problems (e.g., GHG emissions, rainwater leaching, and infiltration of surface water caused by landfilling), and financial problems, such as disposal costs, including the demolition, classification, and transportation of construction waste
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