Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-74-51-K-6

Embedded Intelligence (2V+1U, 4.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 4.0 CP 78 h
2 V Lecture 28 h
1 U Exercise class (in small groups) 14 h
(2V+1U) 4.0 CP 42 h 78 h

Basedata

SWS 2V+1U
CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in SuSe
Level [6] Master (General)
Language [EN] English
Lecturers
Area of study [INF-KI] Intelligent Systems
Livecycle-State [NORM] Active

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)

Contents

This lecture focuses on the basic technologies of Embedded Intelligence, e.g., to acquire information from human beings and the environment, to build models with them and applications on top.
  • Questions, problems to be solved and examples
  • The attributes and application areas of different sensors
  • Different signal processing and machine learning methods for different activity recognition tasks
  • Keypoints to be considered in building the architecture for activity recognition
  • Dynamic sensor configuration
  • Performance evaluation

Literature

Will be given during the lecture.

Requirements for attendance (informal)

None

Requirements for attendance (formal)

None

References to Course [INF-74-51-K-6]

Module Name Context
[INF-74-51-M-6] Embedded Intelligence P: Obligatory 2V+1U, 4.0 LP
Course-Pool Name
[INF-KI_V-KPOOL-6] Lectures of the teaching area Intelligent Systems
[INF-SI_Inf_IntSys-KPOOL-7] Intelligent Systems