Authors:

Nathan Daniel Weston

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

For over a decade, the construction industry has ranked the highest in the number of worker deaths among all industries. New technological developments prompt an opportunity for construction safety to be improved. This ongoing research aims to improve construction safety by incorporating technologies like real time sensors, digital models, and artificial intelligence (AI) models to predict and warn construction workers entering dangerous areas. To accomplish this, a custom GPS system is developed, including a camera, which can detect the location of workers, and a GPS receiver, which will be placed on the camera. The combined information from the camera and GPS receiver can determine the GPS coordinates of workers. These coordinates are uploaded to a digital model of the construction project, which models the workers' positions in real time. Furthermore, an AI model uses these coordinates in the digital model to predict the trajectory of the workers into the near future. Using risk analysis, another AI model determines if a worker might enter a dangerous area. If the model determines the worker is entering dangerous areas, a real time warning is issued to the workers. Early results show the GPS receiver measures coordinates accurately and the camera can detect humans. Also, the digital model can receive real time GPS coordinates. Future research will develop accurate AI models and improve the current GPS system. Also, future research will test on real construction jobsites. Although incomplete, this research shows safety improving technology is integrable on construction sites. Keywords: Construction; Safety; Artificial Intelligence; Digital Twin; Smart Workzone

Source:

Purdue University / 2025

Topics:

No topics listed

Co-authors:

Nathan Daniel Weston