700.461 (13S) Sensor Networks
Überblick
- Lehrende/r
- LV-Titel englisch Sensor Networks
- LV-Art Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 10
- Organisationseinheit
- Unterrichtssprache Deutsch
- LV-Beginn 01.03.2013
Zeit und Ort
Liste der Termine wird geladen...
LV-Beschreibung
Lehrmethodik inkl. Einsatz von eLearning-Tools
Group Works, joint project planning and developmentInhalt/e
Modern offices are full of modern technology but still unaware of its users and their intentions as well as unable to adapt to current situations and actions of its users. The goal of this lab is to develop a smarter office space. Using different sensors like smart cameras, RFID readers or Kinects the office can be made aware of the persons present in the room and the activities they are performing. Based on this knowledge, the smart office can take actions to support the people in their work. Examples are displaying context-specific information (on the topic of the current discussion) on tablets, adapting the behaviour of mobile devices (e.g. auto-muting phones in meetings) or controlling ambient conditions like lighting. In this course, the students will work in groups in order to build a sense-process-act cycle of a Pervasive Computing system. Each group will have the chance to define its own area as well as its own subproject around this area (Depending on availability of hardware, subprojects might be assigned randomly by the teaching staff). The individual subprojects of all groups will be integrated into one large smart office system. Students are expected to work autonomously on their subprojects. Regular joint meetings ensure a targeted progress of all projects. A final integration will be performed at the end of the Semester.Themen
- Sensors and sensor networking
- Context awareness
- Self-adaptation / Self-organisation
Erwartete Vorkenntnisse
Good programming skills in Java, C# or C/C++Prüfungsinformationen
Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.
Beurteilungskriterien/-maßstäbe
Project proposal, autonomous project work, presentations, final interviewBeurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
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Fach: Technischer Schwerpunkt (Pervasive Computing)
(Pflichtfach)
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1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
- 700.461 Sensor Networks (2.0h KU / 3.0 ECTS)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
-
Fach: Technischer Schwerpunkt (Pervasive Computing)
(Pflichtfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
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Sommersemester 2025
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2024
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2023
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2022
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2021
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2020
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2019
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2018
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2017
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2016
- 700.461 KS Sensor Networks (2.0h / 3.0ECTS)
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Sommersemester 2014
- 700.461 KU Sensor Networks (2.0h / 3.0ECTS)