Imagine how much safer your workers would be if you were able to predict when an injury was likely to occur
See what we’ve uncovered in this whitepaper thanks to the data provided by a number of our clients using INX
In this whitepaper:
- Introduction
- Challenge for predictive analysis for injuries
- Attributes and prediction model
- Results and analysis
- Conclusions and future work
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"The objective is to build a system that provides decision support for safety professionals in evaluating injury risks based on historical knowledge of injuries and the conditions they occurred in – an injury risk profile. It is envisioned that machine learning not only can be used to discover the patterns and conditions that lead to increased (although still low) risk of injury, but can also provide insight to a user as to why a particular day or swing is considered to be at increased risk. If successful this could ultimately lead to ‘what-if’ analyses, where a safety professional can suggest alterations to rosters or workloads to see what the effect will be on the learned risk profile – essentially a means of assisting in the prevention of injuries on a dynamic basis, something that cannot be done by procedures alone."
