North Carolina manufacturing professionals may be interested in learning about an ongoing research program that is using cellphones and computer vision technology to improve job safety. Factory workers may be more prone to various musculoskeletal injuries as a result of their employment tasks, which commonly involve repetitive motion. To fight this problem, engineering and industrial systems professors embarked on a project to develop computer vision algorithms that can quantify hand activity. By switching to this method instead of sticking with current standards that involve subjective hazard assessments, the researchers hope to implement a more standardized system of risk measurement.
The University of Wisconsin-Madison study team developed its first algorithms using grants from various government agencies, including the National Institute for Occupational Safety and Health. In September 2016, the team was granted another $1.4 million to continue its work for three more years.
The study team wants to use the grant money to analyze video footage from a broader range of facilities. They think that their pattern recognition techniques might make it easier for engineers to measure injury risks and design workplaces that reduce harm. This solution is simpler than some other methods of analysis, and it has the potential to be used with widely available cell phones and app technology.
Although measurement techniques are improving, understanding workplace injury risks can be a complex undertaking. Even with the advent of new technologies designed to simplify safety processes, employers may still fail to apply the knowledge they gain correctly. Those who continue to work under such conditions may incur injuries that severely limit their future career options or force them to pay for expensive medical aid. Victims who want to file workers’ compensation claims might find it easier to proceed successfully after consulting with an attorney about the documentation that might be necessary.