5-10. Detecting Unsafe Behavior and Measuring Training Effectiveness with AI Image Analysis

AI image analysis is gaining attention as a groundbreaking tool in the EHS (Environment, Health, and Safety) field, as it can detect unsafe behavior in real-time and contribute to more effective training and a better safety culture. Traditional safety management relies on patrols and visual checks, but human attention has its limits, and potential risks are often overlooked. Implementing AI image analysis makes it possible to simultaneously ensure workplace safety and maximize the effectiveness of training.

1. How AI Image Analysis Detects Unsafe Behavior

AI cameras and existing surveillance camera footage are used to automatically detect unsafe actions, such as not wearing a helmet, not using protective equipment, entering a restricted area, or carrying heavy objects with improper posture. Using deep learning algorithms, the system can analyze human movement from the footage and immediately issue an alert for abnormal behavior. This enables employees and managers to instantly grasp risks and take action to prevent accidents.

2. Application for Training

The unsafe behaviors detected by AI can be used as training materials. For example, anonymized real-world footage can be incorporated into safety training to show employees exactly "what actions increased the risk" and "how to improve." Compared to traditional classroom training, using real-life examples enhances learning retention and encourages behavioral change. The data on recurring unsafe behaviors can also be accumulated to identify specific topics for focused training.

3. Benefits and Challenges of Implementation

The benefits of implementing AI image analysis include not only preventing workplace accidents but also making training effectiveness visible and fostering a strong safety culture. It enables 24-hour monitoring, which is difficult for humans, and improves the accuracy of proactive prevention. However, challenges remain, such as the need to protect privacy and address the risk of false positives. Ensuring proper anonymization and improving detection accuracy, as well as gaining employees' understanding and consent, are crucial for success.

4. Future Outlook

It is expected that the fusion of AI and IoT will enable more advanced safety management that integrates image analysis and sensor information. Storing the detection data in the cloud and sharing it with other locations also opens up possibilities for use in global safety training. As AI functions as an "eye" on-site, the establishment of safe behavior and the goal of zero workplace accidents are becoming more tangible.

Conclusion

AI image analysis is a powerful tool that instantly detects unsafe behavior and uses that data for training, deepening a company's safety culture. As a cornerstone of digitalization in EHS management, its adoption is expected to continue to grow.