Data Evaluation and AI

Data analysis, data evaluation and the use of artificial intelligence (AI) are of great importance for the rail industry, as they improve efficiency and safety in particular. 

By analyzing sensor data, AI algorithms can identify patterns that indicate imminent component failure, for example. This allows maintenance work to be planned and carried out proactively before malfunctions or failures occur. AI can also optimize operating data to increase efficiency and reduce environmental impact. 

In conjunction with audio and video content, AI can be used to monitor stations and trains by automatically detecting safety-related events.  

Another way of preventing failures and optimizing maintenance cycles is the synthetic generation of data. This makes it possible to train complex models that simulate real operating scenarios without having to resort to extensive and potentially difficult-to-access real data sets. The use of synthetically generated data not only promotes the development of more robust and efficient algorithms, but also contributes to increasing the safety and reliability of rail transportation by enabling the testing of sensor responses and system integrity under various hypothetical conditions.