All Outputs (3)

Automated code compliance checking through building information modelling (2023)
Journal Article
Aslam, B., & Umar, T. (in press). Automated code compliance checking through building information modelling. Proceedings of the ICE - Structures and Buildings, https://doi.org/10.1680/jstbu.22.00214

Design, construction and handing over of the building need to be complaint with the rules set by the local authority. Manual assessment of the drawings and plans against variable and complex set of rules is quite cumbersome, inconsistent, expensive,... Read More about Automated code compliance checking through building information modelling.

Automated progress measurement using computer vision technology in UK construction (2023)
Journal Article
Bozorgzadeh, A., & Umar, T. (2023). Automated progress measurement using computer vision technology in UK construction. Proceedings of the ICE - Smart Infrastructure and Construction, 176(4), 165-182. https://doi.org/10.1680/jsmic.22.00026

A critical concern with the UK's construction project progress monitoring and control techniques is their dependency on data collection, which is time consuming and unproductive and may lead to various circumstances in managing projects. However, col... Read More about Automated progress measurement using computer vision technology in UK construction.

Structural health monitoring of underground metro tunnel by identifying damage using ANN deep learning auto-encoder (2023)
Journal Article
Abbas, N., Umar, T., Salih, R., Akbar, M., Hussain, Z., & Haibei, X. (2023). Structural health monitoring of underground metro tunnel by identifying damage using ANN deep learning auto-encoder. Applied Sciences, 13(3), 1332. https://doi.org/10.3390/app13031332

Due to the complexity of underground environmental conditions and operational incidents, advanced and accurate monitoring of the underground metro shield tunnel structures is crucial for maintenance and the prevention of mishaps. In the past few deca... Read More about Structural health monitoring of underground metro tunnel by identifying damage using ANN deep learning auto-encoder.