Using AI to Reduce Injuries in Construction


Artificial Intelligence (AI) is playing an increasingly important role in the construction industry, particularly in researching, testing and implementing new methods of improving health, safety and productivity. Today, researchers at the University of Waterloo in Canada are using AI to gain insight into new ways of boosting productivity on construction job-sites by reducing musculoskeletal injuries to masonry workers from wear-and-tear.

Carl Haas and Eihab Abdel-Rahman, engineering professors leading the research efforts at Waterloo, are using motion sensors and AI software to show that expert bricklayers employ previously unidentified techniques to limit the impact on their joints, which is information that can be passed on to apprentices in training programs.

Haas and Abdel-Rahman led two studies. In their first study, sensor suits were used to analyze bodily impact on bricklayers of different experience levels while building a wall with concrete blocks. The data showed that expert masons “put less stress on their bodies, but were able to do much more work” as compared to novices. During their second study, Haas and Abdel-Rahman aimed to understand how master masons work efficiently using “sensors to record their movements and AI computer programs to identify patterns of body position”.

At the conclusion of their research, Haas and Abdel-Rahman found that skilled tradesmen “acquire a kind of physical wisdom that does not follow standard ergonomic rules taught to novices”. For example, they found that workers often “swing” blocks, rather than lifting them, to reduce stress from the “bending of their backs”. Researchers found that by using these unconventional techniques, workers were able to complete tasks twice as fast and with half the effort, while maintaining high quality production.

Moving forward, Haas and Abdel-Rahman plan to conduct an in-depth study using sensor suits to analyze how trainees and apprentices move on jobsites and to provide immediate feedback so that they can modify their movements to further reduce stress and injuries.

Source: engineering.com


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