RailVision collects and stores a huge amount of railway data on a daily basis, using the system’s roof-mounted electro-optical, dynamic and environmental sensors, and is analysed through deep learning.The footage harvested from the sensors is recorded on-board and uploaded from every train to RailVision cloud for cumulative storage.
The offline, captured and analysed data resolves the following objectives:
- Condition monitoring – Measuring and analyzing infrastructure changes and predicting major defects.
- Catenary wires analysis and inspection by measuring changes over time in order to prevent defects along the electrified route.
- Lineside vegetation condition is measured for maintenance and prediction purposes.
- Data collected from many moving environmental sensors simultaneously scattered on a vast area brings a new ability to have a broader insight for environmental analysis and trends.
- All RailVision data is associated to Geographic Information System (GIS) interface, hence the processing outputs are:
- Rail route 2D / 3D modelling
- Simulation and Training for train drivers, operators and dispatchers.
RailVision delivers a range of tools, reports and applications for data archiving, distributed data processing, customer queries and review of results.
Operators, analysts and maintenance researchers are able to search through the databases and perform complex queries to retrieve relevant information, draw out statistical data and build behavioural trends.