Optimizing Railway Systems with RFID and Smart Data in IoT

Abstract

The optimization of railway systems is crucial for enhancing efficiency, safety, and passenger experience in modern transportation networks. This article explores integrating Radio Frequency Identification (RFID) technology and smart data analytics within the Internet of Things (IoT) framework to revolutionize railway operations. RFID technology offers a robust mechanism for real-time tracking and monitoring of assets, including trains, tracks, and cargo. Combined with IoT, it enables the collection of vast amounts of operational data from various sensors and devices embedded throughout the railway infrastructure. RFID technology, increasingly adopted in today's automated landscape, has facilitated multiple functionalities such as contactless payments, tracking, and identification. Wireless sensors and RFID are pivotal in constructing a smart environment. This study explores using an IoT platform to track passengers and facilitate online payments. The tracking system comprises RFID readers capable of locating and monitoring passive and mobile objects with passive RFID tags. Fixing of RFID readers at station entrances and exits, coupled with passengers carrying their RFID tags, facilitates online payments and aids government authorities in crowd monitoring for demand analysis. This innovative approach establishes a digital framework, ensuring adherence to safety regulations for authorities and passengers. A real-time prototype of the system is implemented for practical evaluation. Data collection via RFID tags, acting as transit cards, is analyzed using the DBSCAN algorithm with a Randomized KD-tree to assess spatial and temporal patterns in consumer demand. To enhance performance on datasets, a novel algorithm, iDBSCAN (improved Density-Based Spatial Clustering of Application with Noise), is introduced.