Video and Image Analytics: Digital Eyes on the Rail Assets
Our eyes cannot permanently check the status of all trains or infrastructure – automatic video and image analytics help us to gain efficient comprehensive monitoring.
Quick Facts
- IT or technology background with basic programing skills and Docker knowledge. -
- A Mac, PC or Linux machine (min. 8GB RAM, 20 GB free storage, high performance graphics module) and VM Software (Virtual Box).
Description
- Deepen your understanding of the frameworks for video and image analytics
- Gain insights into example video and image analytics use cases of the Deutsche Bahn Group
- Set up and train your own image analytics service
Course content
Deutsche Bahn has wide track networks, large numbers of stations and other facilities as well as a huge amount of rolling stock. This makes it difficult to have our eyes on everything everywhere at the same time. Meanwhile, fixed maintenance or cleaning schedules are ineffective and not very flexible. Hence, the automatic analyzation of video and image streams allows us to schedule maintenance more flexibly, clean rolling stock when it needed or detect defects before they have a higher impact. As a consequence, we can provide a better, faster and more reliable service to our rail customers.
In this course you will benefit from example use cases from mobility companies and collect practical experience in dealing with the technology by setting up and training your own image analytics application. In this way, you will not only deepen your understanding of the technology, but also learn how to overcome hurdles when dealing with it.
- Introduction to image and video analytics
- Current state of technology and limitations
- Difference to other AI technologies and neural networks
- Use case examples from the Deutsche Bahn Group and other mobility companies
- Setup and training of an image analytics service
IMPORTANT:
To ensure a successful participation in this training, the following requirements need to be fulfilled.
You have:
- Basic programing skills
- Docker knowledge
- A Mac, PC or Linux machine (min. 8GB RAM, 20 GB free storage, high performance graphics module)
- VM Software (Virtual Box)
- A good and stable internet connection
DB Rail Academy focuses solely on offering training courses to larger groups from companies. If you and your company are interested in this course, please contact us via email: db-railacademy@deutschebahn.com so we can plan the next steps with you.