IoT data management in rail

The Device Chronicle spoke to Mathias Beer, Co-founder and CPO at Ci4Rail about the impact of IoT data management and OTA software updates on rail and public transport

In 2020, five founders assembled with rich experience in embedded systems for rail, avionics and industrial automation or “wherever a computer needs to be used in a harsh environment.” They wanted to focus on the rail market. Ci4Rail was born and Co-founder and CPO Mathias Beer and the other founders considered what was the most upcoming thing, the most pressing problem to try to solve in this industry segment. Connectivity had already been largely solved so the management of IoT derived data and helping customers to extract value from their data became their target. Mathias says “Our vision is to see that rail and public transport is the best way for mobility, making it faster, cheaper and more sustainable.”

IoT data management expert Mathias Beer
IoT data management expert Mathias Beer

Mission to enhance IoT data management

Ci4Rail helps organisations in their digital transformation, to get there faster rather than leaving organisations to create knowledge or competences that are not core to their business DNA. Mathias provides an example “Say there is a company that makes cables. It doesn’t necessarily need to have a deep expertise in electronics or in connectivity to the cloud. Through partnership, we can work with that company to make an intelligent cable through collaboration and shared competences.” Ci4Rail develops all its hardware solutions in house. “The cloud application sits in the middle,” Mathias explains. The hardware is also necessary to deliver the intelligence to the edge. “It is necessary to push intelligence to the edges of the network, and we offer a modular and flexible edge computer to be installed in rail vehicles and public transport buses.”

Building blocks for an IoT data management project

Mathias describes how the building blocks are typically put in place for an IoT data management project with a rail vehicle and public transport bus company. He says that you always need an edge computer if you want to decrease the transmission of data from the sensors to the cloud. He explains “Not every sensor is intelligent enough to act as an IoT device. There may be 1000s of devices in a train, sensors that may create analogue values or they may have ethernet-based interfaces, but in no way can they send data to the cloud on their own.”

The first block is the edge computer that needs to be a local data collector, to be close to the sensors, to be close to where the data is generated and to allow pre-processing on the edge. This reduces the number of data going back and forth. There is diagnosis data, for example, where a door controller surfaces a door defect, just a few bytes that can be transmitted. But if you want to measure vibration on the boogie or axis of a train so you can make models out of it, there can be a tremendous amount of data for continuous collection. You can run into 100 gigabytes of data very quickly and you do not want to have to transmit this mammoth amount of data over an LTE connection. Then it is necessary to pre-process the data on the edge, for example, making an FFT over the data to get the spectrum.

The second block is the cloud offering. The measurement data acquired in the train needs to be rooted, filtered and measured for quality. “You do not want to push all data to the analytics, so you need data hygiene. Through a CLI, a user can filter the data. You must keep in mind who owns the data in a train where there may be over 100 subsystems. Is it the train operator, the manufacturer of the door and this is not legally clarified. You can root data sets to different end users of the data. The operator might get 100% of the data, and the sub system provider gets some access to the data through multi-tenancy.”

The third block is device life cycle management and this encompasses monitoring the health status of the devices, and having a robust and secure OTA update mechanism. Mathias points out that IT security will have a massive impact on the rail industry. For example, pushing security patches without having to be present in the vehicle, which is totally unusual now in the rail business, will become a strategic priority. This will be a move away from the rail culture of “Please qualify my asset, and never touch it again.” Mathias believes that security gaps will force operators to provide patches regularly, and quickly. A firmware OTA update will also become normal as doing USB key updates will not be sustainable or desirable going forward. 

Edge computer in IoT data management

The edge computer is a train communication gateway that must be secured with state of the art measures included. It might be vulnerable the day after you sell the system, then you need to be proactive and deliver the patches and guarantee the availability. “CVEs and other vulnerabilities will be continuously checked by Ci4Rail. If there is a problem, Ci4Rail provide patches to our DeviceLifecycle Management. But the final decision to accept and deploy the update comes down to the customers. Because of effect to operation, Ci4Rail cannot be responsible for the final deployment to the train, but we can give the infrastructure and updates.”

The fourth and final block is the application lifecycle management which involves managing all the cloud and edge applications which can be implemented by Ci4Rail, its customers or partners. “Flexible configuration and deployment of distributed applications to edge and cloud is the unique selling point of the KYT System,” Mathias says.

Customers and use cases

Ci4Rail works with major rail providers. The company also works with municipal transport companies who would have lots of different types of vehicles and would need an overall system to take care of this heterogeneous vehicle set. 

The use cases are diverse, from a dedicated problem of a sub system failing. “An electronic control unit reads the voltage from the power line, this could fail and then a cooling solution fails and forces the train to stop. The question becomes “can you include sensors to identify the problem and prevent it from happening?”

Typically at national rail companies, there is a need for an overall management system for fleet management and to make better use of their data. They want good quality data from their trains to the cloud to produce high quality analytics. 

Electro mobility in buses where battery capacity is challenging. The question asked by the engineering planner is how long will the bus battery system last without a recharge? Will the battery power be sufficient for the duration of the route? The question becomes what factors influence the battery life and can you measure them? Is it over-aggressive driving? Is it the route that is impacting the capacity and load? Is it the number of passengers on the bus? A profile of the bus will be created so that battery usage and journey complexion can be better predicted. 

Challenges to progress in IoT data management in rail and bus

The Covid-19 pandemic is causing losses for the rail and public bus sector and this is causing caution in regards to new investments. But Mathias believes that the new investments will come. Data siloing is also a problem, each component or subsystem provider in a train or public bus has their own data. An operator might have to use 16 different systems in 16 different formats. “Operators are afraid of getting rid of partial solutions to get something bigger. They often ask us to integrate into what they have already.” Mathias and his team must work to get beyond this challenge and make gold from the data for the customer. 

We wish Mathias and his colleagues at Ci4Rail well as they continue on their journey of helping rail and public bus companies reap the benefits of digital transformation. 

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