Internet of Things: Making Rail Companies smarter
Rolling stock, infrastructure and technical systems are becoming more and more intelligent and connected so increasing the speed, efficiency and reliability of railway service.
- IT or technology background with basic programing skills (Node.JS is beneficial) and Docker knowledge.
- A Mac, PC or Linux machine (min. 8GB RAM, 20 GB free storage) and VM Software (Virtual Box).
- Broaden your knowledge of the possibilities of the Internet of Things
- Get to know the technical foundation of smart assets
- Gain insights into the best practices of the Deutsche Bahn Group
The Internet of things offers new fields of digitalization in your rail company: Vehicles are becoming more and more intelligent through the use of sensors, telling their status, their operating grade or if they need maintenance. Some of those sensors are even independent from electricity sources: thus creating endless possibilities to smarten up existing assets from times long before the start of digitalization or in far remote places. The resulting data can be used efficiently and enable rail companies to become faster, more efficient and reliable in their service.
In this course you will learn how digital twins of your assets help with your maintenance or to predict future defects. You will examine use cases from mobility companies and collect practical experience in dealing with the technology by setting up your own sensor dashboard. Through this you will deepen your understanding of technology and learn more about how to overcome hurdles in dealing with the new technology.
- Introduction to sensor technology, communication technologies and frameworks
- Use case examples from DB and other mobility companies
- Advantages and limitations of the different technologies
- How to scale in big asset driven companies
- Hands-on: Setting up your own data dashboard with sensor data
To ensure a successful participation in this training, the following requirements need to be fulfilled.
- Basic programing skills (Node.JS is beneficial)
- Docker knowledge
- A Mac, PC or Linux machine (min. 8GB RAM, 20 GB free storage)
- VM Software (Virtual Box)
- A good and stable internet connection
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