Railway monitoring with Vapérail
On-track predictive maintenance.
Data analysis on the edge, closest to the train tracks, brings significant benefits to organizations in the railways industry, even more than anywhere else. With the AI solutions ecosystem from ST, Vaprail developed a smart solution to monitor the conditions of railway tracks with a high confidence level and in real time in order to optimize their maintenance systems.
STMicroelectronicss NanoEdge AI Studio, through its ease of use and the artificial intelligence applied directly in each connected object, enhances our data capture expertise.
Loic TREBUIL
Director Digital AT Vaprail
Approach
This solution can be placed in a strategic location and learn the vibrations of healthy railways in the field over various periods of time, thanks to incremental learning capabilities. The solution can then detect any sign of malfunctioning with a high level of accuracy, so maintenance teams can intervene before any major failures. This is achievable thanks to machine learning algorithms embedded in an STM32 microcontroller, which can communicate thanks to sub-GHz radio embedded on the same chip.
Sensor
Accelerometer from ST
Resources
Model created with NanoEdge AI Studio
A free AutoML software for adding AI to embedded projects, guiding users step by step to easily find the optimal AI model for their requirements.
Running on STM32WL series
The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.
