How do we empower and incentivise people to collect and provide good quality data? Wouldn't it be nice if data is treated as a Utility, as accessible & important as electricity? We aim to research and implement a decentralised framework for producing & consuming data built around rewarding sharing of high quality data. The framework will tackle unique challenges of maintaining data integrity & security of high value assets in the Rail industry.
Transition to Predict and Prevent Maintenance Regimes
Usually maintenance regimes are done in a set duration of time every six months or 1 year. However, there are no indicators that this method is effective or efficient. This duration between maintenance periods could be too short in some cases resulting in excessive maintenance or too long resulting in failures. Our objective is to create an automated system of data collection and analysis that can predict when to conduct maintenance and allows targeted rail track access regimes based on these predictions.
Detection of Geotechnical Failure by means other than Train Drivers and Lineside Staff
Geotechnics is the engineering of various earth materials (soil, ground water and rocks) to make assets like embankments and tunnels to support man-made infrastructures. Currently, the inspection of these assets rely on driver’s experience and staff observation. Our objective is to gain full awareness of the status of structures through real-time information processing by enabling end-to-end automation of asset management including the integration of new maintenance techniques at the design stages.