Predictive monitoring of train wagons conditions using wireless network technologies

Predictive monitoring of train wagons can allow to anticipate possible malfunctioning due to wear and avoid potential accidents. In this paper some network architectures adopting low-power wireless communication technologies are introduced. A performance comparison is provided based on ns-2 simulation results, suggesting that the combined use of WSN and WiFi in a hierarchical architecture is adequate for long trains with several coaches and a large number of sensing nodes.