The Korea Railroad Research Institute (KRRI) has integrated and demonstrated 12 preventive railway safety technologies that utilize artificial intelligence (AI) to predict the likelihood of human error among railway workers and detect on-site risks in real time. The institute plans to expand field demonstrations for railway operators and establish a regulatory framework for practical safety management applications.
According to KRRI, a demonstration event showcasing core preventive railway safety technologies was held on October 26 at its Osong branch, attended by over 30 officials from the Ministry of Land, Infrastructure and Transport and related railway organizations.
The technologies demonstrated included AI video analysis for detecting risks among train operators and track workers, biometric signal measurement, job suitability assessments, smart safety equipment, safety management for emergency and power outage operations, AI-based predictions of human error probabilities, and integrated safety management based on digital twins.
KRRI showcased a comprehensive process linking AI, video, biometric, and location data with on-site work management systems, covering everything from work preparation to risk assessment, work approval, and real-time safety monitoring and response. The system evaluates the potential for human error by analyzing worker locations and surrounding environments, displaying any abnormal situations, such as area breaches, on a digital twin interface.
For instance, a non-contact AI biometric measurement gate automatically checks workers' body temperature, heart rate, and alcohol levels. Location tracking technology is used to monitor railway workers' real-time positions and confirm entry into hazardous areas.
In June, KRRI also unveiled key technologies from two research projects at the National Land and Transportation Technology Fair, including AI biometric measurement devices, virtual training platforms, and predictive technologies analyzing railway accident, disruption, and vehicle and facility data using AI.
However, these technologies have not yet been widely implemented in actual railway operations. KRRI stated that it aims to expand field demonstrations with railway operators based on this demonstration and establish a regulatory framework to incorporate these technologies into national railway safety policies and safety management practices.
Park Chan-woo, a senior researcher at KRRI, noted, “We have presented the technical possibilities for managing human error and on-site risks among railway workers by linking individually developed railway safety technologies according to actual work procedures. We will promote technology advancement and institutional connections to expand field demonstrations and support safety management decision-making.”
* This article has been translated by AI.
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