AI and Digital Twin Technology Set to Transform Worker Safety in Industrial Environments
Scientists worldwide are researching a new way to assess employee safety in factories (not excluding those that manufacture gas or oil). Worker safety monitoring has been given an impetus by deploying Human Digital Twin (HDT) technologies and AI methods of a higher order.
The research aims to establish a system for monitoring activities where workers interact. This is to be completed using real-time monitoring and analysis mechanisms, the outcome of which should be physical, mental, and emotional status conditions within an integrated perspective that incorporates these three elements simultaneously. The way is open to investigating how much digital twins have contributed significantly within Industry 5.0, thus indicating their importance as well.
The framework’s main component is creating a caring evaluator chatbot to detect emotions in written dialogues through natural language processing (NLP). Furthermore, emotions will be extracted from video logs using oratory and facial expression analysis and personality tests. All these forms of analysis have been introduced to enable a holistic comprehension of an employee’s psyche issues, including their anxiety level.
This extraordinary structure aims to recognize stress and other emotional issues, such as anxiety, that pose a danger to employees. Although this research lacks case studies or applications from real-life scenarios so far, it sets the stage necessary for the future application of these technologies.
These insights are not just theoretical. They are aimed at providing practical applications for development, thereby making work environments safer and more encouraging. The transformative potential of artificial intelligence (AI) and digital twin (DT) technology is demonstrated by this innovative method.