Science

Workers in the sheep shearing industry are using motion sensors and AI to lessen injuries


Workers in Australia’s sheep shearing industry are being tracked with motion sensors as part of an effort to lessen workplace injury rates

  • Australian sheep shearers are six times more likely to be injured on the job
  • Researchers from the University of Melbourne are tracking their posture
  • Early findings suggest sheep shearers don’t take enough breaks
  • They also put off shearing strong rams til the end of the week, when workers are most tired and more susceptible to injury 

A new research project in Australia is using motion detectors and muscle sensors to track sheep shearers in an effort to minimize on the-job-injuries.

Sheep shearers are six times more likely to be injured in the workplace than the average Australian worker. 

Data from sensors attached to sheep shearers will be used to model worker movement throughout the workday and test new ways of doing the job without risking injury. 

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A new data collection program from the University of Melbourne and Australian Wool Innovation hopes to lessen the injury rate among sheep shearers, who are six times more likely to be injured on the job than the average Australian worker

A new data collection program from the University of Melbourne and Australian Wool Innovation hopes to lessen the injury rate among sheep shearers, who are six times more likely to be injured on the job than the average Australian worker

The study, a joint project between University of Melbourne and the trade group Australian Wool Innovation, uses sensors to measure electrical activity in muscles.

These sensors are placed directly on the skin of the lower back and upper thighs, the ABC reported, while motion detectors are placed around the joints to track a worker’s posture and shearing motions.

Unsurprisingly, workers build up muscle fatigue at the end of each work day, and it continually builds throughout the week.

‘The shearing position means you’re bent over a lot for six hours a day and staying in that position leads to a lot of injuries,’ University of Melbourne’s Mark Robinson said.

The researchers are using data from sensors that measure muscle activity and general limb motion to track sheep shearers' posture and precision of movement throughout the workday

The researchers are using data from sensors that measure muscle activity and general limb motion to track sheep shearers’ posture and precision of movement throughout the workday

‘Back injuries are a particularly problem for shearers because they take such a long to rehabilitate and it makes the cost of these injuries twice as high as a regular injury.’

Though the team is still gathering data, they have suggested a few preliminary changes that could have an effect. 

One change would be to shear rams, which are typically the heaviest and hardest to deal with, at the beginning of the work week instead of putting them off until the end of the week, which is the current custom.

Another simple change would be to add more frequent breaks to avoid building up muscle fatigue might also be effective.

‘It may mean the traditional smoko [slang for ‘smoke break’] needs to be changed and be customized to the rest period for every individual shearer,’ AWI’s Jane Littlejohn said.

Early findings suggest shearers could take breaks more frequently and also deal with rams at the beginning of the week instead of the end

Early findings suggest shearers could take breaks more frequently and also deal with rams at the beginning of the week instead of the end

‘It may also be that a shearer wears a device and that device is tuned into the fatigue signals in the muscle and commences extra force on the body that takes the stress of the shearer.’

Similar tracking hardware is in current use to track factory workers in the US.

The Brooklyn-based startup Strongarm Technologies Inc. has developed a motion tracking harness that’s currently in limited use with factory and warehouse workers for Walmart, Heineken, and Toyota, among others.



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