Environmental Health and Safety (EHS) training is an integral part of many industries, aimed at minimizing hazards and risks in the workplace. The traditional methods of EHS training involve classroom sessions, safety drills, and on-the-job training. While these methods have been effective in many ways, they have their limitations. However, with the advent of Artificial Intelligence (AI) and Computer Vision, the landscape of EHS training is set to change forever.

AI-powered EHS training can be broken down into two broad categories - automated observation and risk prediction. Let's look at each of these categories in more detail.

Automated Observation

Automated observation refers to the use of AI-powered cameras to monitor the workplace for potential hazards. These cameras can detect unsafe behaviors, such as workers not wearing appropriate personal protective equipment (PPE), and notify the concerned authorities. They can also monitor the usage of equipment and machinery to ensure that they are being used safely.

Automated observation also enables employers to collect data on workplace incidents and accidents, which can be used to identify patterns and make informed decisions to prevent future incidents.

Using AI and computer vision, employers can automatically gather evidences of unsafe acts for workforce EHS meetings. The AI algorithms can analyse the data collected from the cameras and sensors to identify unsafe behaviors and provide real-time feedback to the workers. This information can then be used to conduct EHS meetings with the workforce to address the identified unsafe behaviours and ensure that the workers understand the importance of following safety protocols.

Risk Prediction

Perhaps the most significant impact of AI and computer vision on EHS training is in risk prediction. By analyzing data from various sources, including sensors, cameras, and incident reports, AI algorithms can identify potential hazards and predict the likelihood of workplace incidents.

This data can then be used to develop targeted EHS training programs that address specific risks and help prevent accidents. For instance, if the data shows that workers are at a higher risk of falls from height, employers can develop training programs that focus on fall protection.

Conclusion

AI and computer vision have the potential to revolutionize EHS training forever. Automated observation and risk prediction can significantly reduce the number of workplace incidents and injuries, and improve overall safety in the workplace. Additionally, AI-powered EHS training can be customized to specific industries and workplace environments, making it more effective than traditional training methods. With the ability to automatically gather evidences of unsafe acts for workforce EHS meetings, employers can address the identified unsafe behaviors and ensure that workers follow safety protocols, making the workplace safer for workers everywhere.