This study delineates the development of a safety management system, leveraging Information and Communication Technology (ICT), specifically designed for workers at offshore wind power plants.
In the current epoch, the global community is witnessing a...
This study delineates the development of a safety management system, leveraging Information and Communication Technology (ICT), specifically designed for workers at offshore wind power plants.
In the current epoch, the global community is witnessing a paradigm shift towards carbon neutrality, with numerous nations and corporations establishing and striving towards net-zero targets. This shift necessitates a
transition to sustainable energy systems, a critical task for the future of South Korea. Offshore wind power generation, in this context, emerges as a pivotal solution, offering environmental benefits as a renewable energy source and potential contributions to energy security and the establishment of
sustainable energy systems.
The principal objective of this research is the continuous enhancement of safety for workers operating in offshore wind power plants. To achieve this, we developed a location tracking and safety management system, incorporating a machine learning-based algorithm. This system utilizes sensor data to automatically identify human behavior, thereby enabling a more precise prediction of the behavior and status of offshore wind power plant workers. This predictive capability facilitates improved behavior pattern analysis and augments accident prevention rates.
The findings of this research are anticipated to contribute significantly to the enhancement of safety in offshore wind power plants and bolster the advancement of sustainable energy generation.