A Study on the Development of an IoT Sensor Data Acquisition Device for Railway trackside facility maintenance and worker safety

This paper presents the design and implementation of an all-IP–based IoT sensor data acquisition device tailored for railway trackside environments. The proposed system is developed with three primary objectives: Integration, enabling seamless aggregation and standardized processing of heterogeneous sensor data; Scalability, ensuring flexible interoperability with diverse sensor types through a unified hardware and communication architecture; and Maintainability, supporting efficient remote monitoring, diagnostics, and control for field maintenance operations. The device enables the transition from conventional periodic inspection practices to a real-time condition-monitoring and predictive-maintenance framework. By supporting proactive fault detection and enhancing trackside safety management, it contributes to improved operational reliability and reduced maintenance costs. Furthermore, the results of this study establish a technological foundation for advanced railway applications—including digital-twin systems, data-driven analytics, and AI-based predictive maintenance—demonstrating the potential of the proposed device for future expansion within intelligent railway infrastructure management platforms.