EVALUATION OF WALL EVENNESS USING DEPTH SENSOR FOR BUILDING QUALITY ASSESSMENT

Authors

  • Ahmad Zaki Shukor Faculty of Electrical Technology and Engineering, UTeM, 76100, Durian Tunggal, Melaka, Malaysia
  • Muhammad Afiq Zailani Faculty of Electrical Technology and Engineering, UTeM, 76100, Durian Tunggal, Melaka, Malaysia
  • Muhammad Herman Jamaluddin Faculty of Electrical Technology and Engineering, UTeM, 76100, Durian Tunggal, Melaka, Malaysia
  • Mohd Zulkifli Ramli Faculty of Electrical Technology and Engineering, UTeM, 76100, Durian Tunggal, Melaka, Malaysia
  • Ghazali Omar Faculty of Electrical Technology and Engineering, UTeM, 76100, Durian Tunggal, Melaka, Malaysia
  • Syed Hazni Abd Ghani Construction Quality Assesment Centre (CASC), Construction Research Institute of Malaysia (CREAM), Malaysia

DOI:

https://doi.org/10.11113/jurnalteknologi.v88.23439

Keywords:

Quality Assessment System, Building Construction Works, Internal works, depth camera, Mecanum wheels

Abstract

The advancement of computing technology has spearheaded the change in the industry nowadays. Due to high speed processors which improves processes in industries, the construction industry has also adopted the Industry 4.0 via the Construction 4.0 Strategic Plan. Not only robots and its advanced technology impacted the assembly process in construction, it has also encouraged technologies to be applied in the quality assessment process, i.e. after a building has completed construction. The quality assessment robot is proposed in this paper, to address the wall evenness assessment as one of the criteria in the Internal Works from the Construction Industry Standards 7 (CIS7). It uses an Intel Realsense L515 LIDAR depth camera fitted onto a mobile robot, which houses a MiniPC, mobile robot controller and four 60mm mecanum wheels. The results of the assessment shows a promising 92.3% accuracy, which shows the viability of the proposed assessment method that could measure a 60cm x 50cm wall depth image from a 70cm center distance from the depth camera.

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Shukor, Ahmad Zaki, Mohd Hadi B. Jamaluddin, Mohd Zulkifli B. Ramli, Ghazali B. Omar, and Siti Hajar A. Ghani. 2022. “Internal Works Quality Assessment for Wall Evenness Using Vision-Based Sensor on a Mecanum-Wheeled Mobile Robot. International Journal of Advanced Computer Science and Applications. 13(6): 172–79. https://doi.org/10.14569/IJACSA.2022.0130622.

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Published

2025-12-23

Issue

Vol. 88 No. 1: January 2026

Section

Science and Engineering

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