AUTOMATIC INDOOR CONSTRUCTION PROGRESS MONITORING : CHALLENGES AND SOLUTION

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A4 Artikkeli konferenssijulkaisussa

Authors

Chauhan, Inshu
Seppänen, Olli

Date

2023

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en

Pages

7

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Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference, Proceedings of the European Conference on Computing in Construction

Abstract

Indoor construction progress monitoring has challenges like occlusion, light variation, dynamic environment which makes its automation different from outdoor construction progress monitoring. AI/deep learning approaches can help overcome these challenges but using them for indoor construction monitoring raises some issues like lack of annotated image data for construction works. Transfer learning provides the initial solution to the AI related challenges. In our research we use this stateof-the-art method on construction site data and detect asbuilt stages of a drywall construction. The results are promising with accurate prediction of 3 stages of the drywall process.

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Publisher Copyright: © 2023, European Council on Computing in Construction (EC3). All rights reserved.

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Chauhan, I & Seppänen, O 2023, AUTOMATIC INDOOR CONSTRUCTION PROGRESS MONITORING : CHALLENGES AND SOLUTION . in M Kassem, L C Tagliabue, R Amor, M Sreckovic & A Chassiakos (eds), Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference . Proceedings of the European Conference on Computing in Construction, European Council on Computing in Construction (EC3), European Conference on Computing in Construction and the 40th International CIB W78 Conference, Heraklion, Greece, 10/07/2023 . https://doi.org/10.35490/EC3.2023.225