Numan Khan

TL;DR: The proposed automatic safety rule compliance approach for excavation works leveraging algorithmic modeling tools and BIM technologies has potential to help the designers through automated modeling and assist decision makers in developing productive and practical safety plans compared to the conventional 2D plans for excavation work at the preconstruction phase.

TL;DR: In this article , a real-time hybrid vision-and IoT-based system for safety engineers to monitor the use of safety hooks at risky elevations in realtime is proposed, which can help safety managers by efficiently automating multiple workers' safety monitoring in real time at complex construction sites where performing a hazardous activity at a risk height may lead to FFH fatality.

TL;DR: A correlation-based approach for mobile scaffold safety monitoring and detecting worker's unsafe behaviors using a deep neural network and object correlation detection (OCD) module, which confirms the Mask R-CNN-based OCD module's applicability for detecting worker't unsafe behavior effectively in a construction environment.

TL;DR: A visual language approach for rule translation and a multi-agent-based construction fire safety planning simulation in BIM has the potential to helps the designers through its effectiveness and convenience while it could be helpful in the field for practical use.

TL;DR: A novel hazard identification approach through spatial–temporal exposure analysis called HISTEA, which integrated scenario analysis of accident cases into 4D building information modeling (BIM) to proactively aid project teams in detecting hazards that ultimately reduce repetitive accidents caused by overlapping activities.