Machine Learning on the Edge
Image processing and analysis in the Industry 4.0 environment
With increasing digitalization, companies manage a steadily growing stock of data in many areas of their operational business. This includes, for example, access information to websites, sales figures or even sensor information recorded by machines in production. These data volumes pose an increasing challenge in the industrial environment, since they must first be transferred to appropriate computers before they can be analysed. This can be difficult in terms of bandwidth and occurring signal failures. As a result, the context and meaning of this information can only be captured inadequately and with a high level of effort by employees.
The trend is moving away from centralized evaluation to decentralized processing of data at the point of collection. This architecture, known as Edge Computing or Edge-AI (Artificial Intelligence), allows the network nodes collecting data to perform on-site analyses, and only the interpretations of the situation and states are forwarded. This core information can also be transmitted with limited bandwidth. The course provides general basics of machine learning and AI-supported image processing.
After the seminar, you will...
Know how to understand basic machine learning procedures.
Know how to implement simple Edge-AI procedures.
Understand Edge-AI challenges.
Be able to define application requirements for machine learning approaches.
This seminar offers you an introduction into...
Selected Edge-AI topics.
Selected topics like Edge-AI.
The Edge Computing Paradigm.
The target groups are...
Developers of machine learning solutions
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