Intelligent Hazard Detection

Intelligent Hazard Detection (i-HaD) system is developed to exploit onsite images captured by CCTV surveillance cameras or site personnel to automatically identify and predict if physical health or safety of personnel at site is, or likely to be at risk. This project evaluates i-HaD by focusing on one of the popular construction hazards, that is the construction dust which leads to severe health issues especially on the long-term. Dust generated by many construction activities has been a persisting threat to physical health of construction workers for decades. To automate the identification of dust generated at construction site, an object detection method is used with the help of a Convolutional Neural Network (CNN) and faster R-CNN in order to detect dust generating tools (e.g.: cut-off saws, grinders and drillers) as well as the workers’ PPE (e.g.: respirator) and material involved (e.g.: concrete) from an input of dataset of construction site images. The project presented a step towards the digital transformation and automation of the health and safety related tasks within the construction domain in order to achieve the ultimate goal of creating a safe environment for construction personnel. 

 

External Partners: Arcus Consulting 

Lead Academics' on This Project

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