This article discusses how artificial intelligence (AI) and computer vision can support organizations in achieving occupational health and safety (OHS) accreditation goals effectively and efficiently, highlights the importance of giving the OHS team the necessary resources to achieve accreditation and suggests AI-driven computer vision as a solution. It also explores how computer vision can support the four headings of the Plan-Do-Check-Act (PDCA) model that forms the structure of ISO management standards and other accreditation schemes.
Under the Plan stage, the article explains that computer vision can provide constant monitoring and feedback on activities that may lead to accidents or injuries. This makes it possible to set new OHS objectives based on a preventative approach.
For the Do stage, the article suggests that computer vision can collect and store short, time-stamped, geo-located video clips of processes, making it practical to maintain documented information necessary for process assurance.
Regarding the Check stage, the article suggests that computer vision can monitor activities where hazards have been identified and check the effectiveness of controls. This makes it possible to identify potential risks and address them before accidents occur.
Finally, under the Act stage, the article recommends the use of AI to manage the overwhelming amount of information generated by computer vision. Automated workflows make sure the right people receive information, and AI-generated safety reports provide evidence of an organization's continual improvement.
In conclusion, this article highlights the potential benefits of using AI and computer vision to support OHS accreditation goals effectively and efficiently. By providing constant monitoring and feedback, automating workflows, and generating safety reports, computer vision and AI can help organizations achieve their accreditation objectives and maintain the safety of their workforce.
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