According to recent pwc main inovation research, the rail sector has been deemed the leader using IoT for predictive maintenance. With what seems like a growing number of train accidents, the rail sector has been under constant pressure to improve the safety and reliability of its infrastructure.
The rail sector has always had a complex network of sensors, signals, and rail mechanisms, but traditionally they have not been interconnected. As digital assets become smarter, the sector has been under pressure to build out more innovative condition monitoring solutions. For instance, traditionally the speed of a train has not been correlated directly with the long term condition of bridges. Using data collected from a train’s speed and bridge’s vibration data, it is possible now to run machine learning models to determine optimal conditions or maintenance schedules. However, many other challenges arise, where data will need to be captured and analyzed to react in real-time, whether it is sensors on railway ties; overhead cameras; pantographs of passing trains; sensors for detecting overheating in shaft sleeves; or fluctuation in power consumption, which often signals an imminent failure in a switch.
IoT Use Case
Deploying interconnected and smarter assets on the edge will enable the rail sector to significantly improve the way it analyzes data and reacts to issues. Augmate Connect will work with the rail sector to manage its digital assets. By creating policies in Augmate Connect, a rail company will be able to interlink assets that share crucial dependencies. Since the company will be managing the entire fleet of digital assets in Augmate Connect, they will be able to capture and model data, which will help determine correlations between assets that may have not been obvious. In order to comply with regulatory safety reporting/ auditing, a company may opt to share some of its asset data through Augmate Connect’s distributed ledger solution with the regulators.