Der Winter naht, und zum Glück müssen wir uns nicht vor den Weißen Wanderern fürchten. Was wir aber im Auge behalten sollten, sind die bei den kalten und strengen Wetterbedingungen immer häufiger auftretenden Batterieausfälle an Lokomotiven.
Railway operators are now able to better understand the driver’s experience, follow up on the condition of their rolling stock during service, and provide accurate diagnosis and actions from the control room.
As a railway operator and transit authority, the temptation of predictive maintenance, IoT and AI is often irresistible. However, it's important not to lose sight of what's reality and and what's fiction.
How can edge computing be used in rail: from failure detection to in-service support and usage-based maintenance.
Remote monitoring equipment developed by Railnova is providing a centralised system for fleet diagnostics and is now in use on more than 1000 locomotives and trains across Europe. It is also supporting the shift to predictive train maintenance.
As an increasing number of people are choosing to travel by train and lines are getting busier, it’s paramount to prevent anything that might cause delays and to be very responsive in case of unforeseen events.
Railnova’s CEO Christian Sprauer was featured in CNBC’s IOT: Powering the digital economy documentary alongside the Head of Digital Innovation at BMW.
Fuel consumption and fuel supply are central aspects of diesel fleet management. Railnova monitors fuel gauge signals to automatically inform operators of relevant events, such as when a locomotive is running low on fuel and when it has been refuelled.
Interview: the inside story on how the startup Railnova is helping rail companies transform their fleet management and maintenance.
Growing a startup in rail is not as simple as growing one in a consumer-oriented sector, it's far more complex due to the many regulations, the importance of safety and long held traditional practices.
A day in the life of two Railnovians: helping Railway organisations access data and act on predictive alerts
What better way to give you an insider view on what Railnova does, than having two members of the team share how they are contributing to the process of accessing data on trains and translating that data into actionable insights and predictive alerts?