IoT Integration in Railway Signaling Systems: Opportunity Analysis and Application of Track Guard Fatigue Monitoring (Pjl)

Abstract

The integration of IoT into railway signalling offers a transformative opportunity to enhance safety, particularly at level crossings. Traditional mechanisms relying on scheduled maintenance often fail to address real-time human-factor risks like operator fatigue. This manuscript analyzes IoT integration to monitor the alertness of Level Crossing Guards (PJL), proposing a shift from reactive to proactive safety management. The core problem is the lack of continuous, objective systems to detect fatigue, as conventional methods like self-reporting are intermittent and subjective. The objective is to utilize IoT technologies—sensor networks, data analytics, and wireless communication—to develop a reliable, non-intrusive fatigue monitoring application. The proposed methodology involves a multi-layer architecture where wearable sensors collect physiological data. This data is transmitted via low-latency protocols like LoRaWAN to a central unit, where machine learning algorithms assess fatigue levels in real-time. The system interfaces with signalling infrastructure to trigger automated alerts or backup protocols when critical thresholds are detected. Anticipated results indicate a paradigm shift, significantly reducing accident risks through continuous vigilance and data-driven decision-making. Beyond safety, collected data can optimize shift patterns and wellness programs. Despite challenges regarding privacy and costs, IoT-based fatigue monitoring is concluded to be a feasible, highly impactful application. Its success could serve as a model for enhancing human-factor safety across critical transport domains, moving towards intelligent railway ecosystems.