AI in Embedded Systems

Description

Learning outcomes MMK1 Scientific-disciplinary knowledge and comprehension in the field of Artificial Intelligence MMP1 To make operational Objectives Embedded systems have become much more prominent over the past years in our lives.  Within embedded systems machines, devices or simple objects are provisioned with electronics hardware and software to capture, process and gather data.  In combination with AI, these “smart objects” or “smart devices” can be made intelligent.  In this course, the student will lean how AI methods can be applied in embedded systems in order to give “smart objects” a self-learning capability and can support humans in the decision making. The  student understands what embedded systems are and knows the importance in our society.  The student also understands the need to build AI applications in these embedded systems and can summarize the different challenges.  The student can build these AI applications by adjusting traditional AI algorithms.  The student also has extensive knowledge of dedicated hardware solutions and hardware architectures for AI applications.  The student is also able to provide solutions and describe them to problems given through different use cases.