Qulsar’s customer was a leading organization providing services for rail infrastructure, ensuring maintenance and safety through regular inspections of a rail network in the UK. To improve their ability to complete proactive preemptive maintenance, the customer outfits special trains with high definition cameras, ultrasonic equipment and vibration sensors, and these trains travel across the UK’s rail network collecting detailed data on the track and the underlying ground. The large volume of data is stored and then offloaded at specific stations to be processed offline.
The customer had a challenge with organizing this growing volume of data from its sophisticated sensitive sensors in a meaningful and useful manner. The problems encountered were:
Qulsar’s engineers planned to deploy a precision timing platform for its on-train sensor fusion platform. This seamless solution helped to give them real time data with precise and high quality time-stamps. These time stamps gave the data rich context and enabled the expert system to inter-relate data from different sensors. System wide actionable deductions about track health could be made and detecting the anomalies and predictive track maintenance became much simpler. There was also reduced dependence on off-line cloud processing.
In this case, Qulsar’s robust solution not only helped with a reduced deployment cost, but also helped with: