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As rail transit continues to develop, expanding railway networks increase the demand for sustainable energy supply and intelligent infrastructure management. In recent years, advanced rail self-powered technology has rapidly progressed toward artificial intelligence and the internet of things (AIoT). This review primarily discusses the self-powered and self-sensing systems in rail transit, analyzing their current characteristics and innovative potentials in different scenarios. Based on this analysis, we further explore an IoT framework supported by sustainable self-powered sensing systems including device nodes, network communication, and platform deployment. Additionally, technologies about cloud computing and edge computing deployed in railway IoT enable more effective utilization. The deployed intelligent algorithms such as machine learning (ML) and deep learning (DL) can provide comprehensive monitoring, management, and maintenance in railway environments. Furthermore, this study explores research in other cross-disciplinary fields to investigate the potential of emerging technologies and analyze the trends for future development in rail transit.
Tang et al. (Mon,) studied this question.