DOI QR코드

DOI QR Code

Estimation Method of the Amount of Demolition Waste through Automated Calculation of Volumetric Spaces using Drones

드론 활용 체적산출 자동화를 통한 해체 폐기물량 예측기법에 관한 연구

  • Ryu, Jung-Rim (School of Architectue, Kyungpook National University) ;
  • Kim, Hye-Ri (School of Architectue, Kyungpook National University) ;
  • Park, Won-Jun (Department of Architectural Engineering, Kangwon National University)
  • Received : 2022.10.24
  • Accepted : 2022.11.25
  • Published : 2022.12.20

Abstract

In this study, the process of drone photography, automatic volume calculation, total floor area conversion, and waste calculation was constructed as a QGIS plug-in to predict the demolition waste (DW) generated in an aged area where drawing information or building information is uncertain. Through a case study, the high consistency between the automatically calculated volume using the drone and the BIM volume based on the field measurement was confirmed. Field application was carried out for the planned demolition work site, and the consistency between the drone-based volume and the actual measurement-BIM-based volume was reconfirmed. The waste generation unit was applied and the amount of DW was calculated by setting the floor height and building type, and the entire process was completed within 6 hours. Although the difference between building information and building objects through drones occurred according to the setting of temporary structures, loads, and floor heights, it was found that the actual amount of DW was generated more than the initial estimate. It is expected that measures to improve the accuracy of volume and floor area conversion will be required through case studies in the future.

본 연구에서는 도면정보나 건축물 정보가 불확실한 노후 지역의 건설폐기물 발생량 예측을 위하여 드론촬영, 자동 체적 산출, 연면적 간접 변환, 폐기물량 예측의 과정을 QGIS 플러그인 형태로 구축하였다. 이를 위해 모의검증을 통하여 드론 활용 자동 산출된 체적과 현장실측 기반 BIM 체적과의 높은 일치성을 확인하였다. 실제 해체예정지를 대상으로 현장검증을 실시하고 드론 기반 체적과 실측-BIM기반 체적의 일치성을 재확인하였다. 층고와 건축물 유형 설정을 통하여 폐기물 발생 원단위를 적용하고 직간접적인 방식으로 폐기물량을 산출하였고, 전체 과정은 드론 촬영과 산출 자동화 과정을 포함하여 면적 1,200,000m2 대상지를 6시간 이내의 작업시간으로 신속하게 처리하였다. 비록 건축물 정보와 드론을 통한 건물 객체의 차이는 가설물, 적재물, 층고 설정에 따라 오차가 발생하였지만, 실제 해체물량도 최초 예측보다 더 크게 발생할 것으로 파악되었으며, 향후 사례조사를 통하여 체적-연면적 변환의 정확도 향상에 대한 개선이 필요할 것이다.

Keywords

Acknowledgement

This paper was written based on the academic conference presentation(corresponding to references No. 4 and No. 6).

References

  1. Ryu JR, Kim HR, Park WJ. New approach to prediction and management of construction waste generation. Proceeding of Korean Recycled Construction Resources Institute. 2019 Nov 22, Korea. Jeju (Korea): Korean Recycled Construction Resources Institute; 2019. p. 207-8.
  2. Yoo HT, Chi SH, Kim JY, Kwon TG. A preliminary method for disaster waste volume estimation based on UAV image post processing. Proceeding of Korean Society of Civil Engineers; 2016 Oct 19-21; Jeju, Korea. Seoul (Korea): Korean Society of Civil Engineers; 2016. p. 11-2.
  3. Akinade OB, Oyedele LO, Ajayi SO, Bilal M, Alaka HA, Owolabi HA, Arawomo OO. Designing out construction waste using BIM technology: Stakeholders' expectations for industry deployment. Journal of Cleaner Production. 2018 Apr;180:375-85. https://doi.org/10.1016/j.jclepro.2018.01.022
  4. Ryu JR, Kim HR, Kim YC, Kim HM, Park WJ. Automated DSM-based building volume calculation for predicting construction waste. Proceeding of Korean Recycled Construction Resources Institute; 2019 Nov 22; Jeju, Korea. Seoul (Korea): Korean Recycled Construction Resources Institute; 2019. p. 209-10.
  5. Kim HR, Ryu JR, Kim JW, Park WJ. Development of volume-based automated prediction system for construction waste using DSM. 2019 Summer Conference of Society for Computational Design and Engineering; 2019 Aug 19; Jeju, Korea. Seoul(Korea): Society for Computational Design and Engineering; 2019. p. 160-1.
  6. Ryu JR, Kim YC, Park WJ. Application of DSM in predicting construction waste quantity. Proceeding of Korean Recycled Construction Resources Institute; 2019 Apr 3-5; Kangwon, Korea. Seoul (Korea): Korean Recycled Construction Resources Institute; 2019. p. 47-8.