Selected topics in Pervasive Computing (Winter 2013/2014): Difference between revisions

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|credits=180h, 6 ECTS
|credits=180h, 6 ECTS
|module=M.Inf.1221: Spezielle fortgeschrittenen Aspekte der Telematik
|module=M.Inf.1221: Spezielle fortgeschrittenen Aspekte der Telematik
|lecturer=[http://www.stephansigg.de Stephan Sigg]
|lecturer=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&purge=y&personal.pid=128205 Stephan Sigg]
|ta= --
|time=Wednesdays, 10.15 - 11.45. (Note: First meeting on 30.10.2013, see #Schedule below); Exercise: 16:15 - 17:45 (bi-weekly)
|time=Wednesdays, 10.15 - 11.45. (Note: First meeting on 30.10.2013, see #Schedule below); Exercise: 16:15 - 17:45 (bi-weekly)
|place=IfI 3.101
|place=IfI 3.101
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** [[Media:SAPC_07.pdf | Security - cont. (pdf)]]
** [[Media:SAPC_07.pdf | Security - cont. (pdf)]]
* Wednesday, '''January 29th, 2013, 10.15 - 11.45''': Session 9
* Wednesday, '''January 29th, 2013, 10.15 - 11.45''': Session 9
** [[Media:SAPC_08.pdf | Context prediction (pdf)]]
* Wednesday, '''February 5th, 2013, 10.15 - 11.45''': Session 10
* Wednesday, '''February 5th, 2013, 10.15 - 11.45''': Session 10
** [[Media:SAPC_08.pdf | Context prediction - cont. (pdf)]]
* Wednesday, '''February 5th, 2013, 16.15 - 17.45''': Exercise 5
* Wednesday, '''February 5th, 2013, 16.15 - 17.45''': Exercise 5


Latest revision as of 18:05, 11 September 2014

Details

Workload/ECTS Credits: 180h, 6 ECTS
Module: M.Inf.1221: Spezielle fortgeschrittenen Aspekte der Telematik
Lecturer: Stephan Sigg
Teaching assistant: --
Time: Wednesdays, 10.15 - 11.45. (Note: First meeting on 30.10.2013, see #Schedule below); Exercise: 16:15 - 17:45 (bi-weekly)
Place: IfI 3.101
UniVZ [1]


Course Overview

The course will address selected topics in Pervasive Computing. This semester the main focus of the lecture will be on activity recognition from sensor-data of mobile and distributed devices. In addition, other fields of Pervasive Computing are covered to provide students with a good overview on current advances and research challenges. Depending on the interest of the students, the emphasis on these additional topics may differ.

Possible course topics (focus according to interest of students):

  • Activity recognition
    • Fundamentals of pattern matching
    • Features and feature extraction
    • Feature subset selection
    • Polynomial curve fitting
    • Parzen estimator
    • k-NN
    • SVM
    • ANN
  • Context prediction
    • Operations for single- and multi-dimensional context data
    • Prediction architectures
    • Context processing operations
    • Prediction algorithms
      • ARMA
      • Kalman filter based
      • Approximate pattern matching
      • Markov predictors
      • Prediction with independent/principal component analysis
      • SOM
      • IPAM
      • ONISI
  • Security with noisy data / context-based security
    • Entropy
    • One-time-pad
    • Random number generators
    • Statistical tests
    • Fuzzy commitment
    • Fuzzy extractors
    • PUFs
  • Networked objects
    • A generic sensor node
    • Sensor networks
    • Communication protocols
    • Collaborative and cooperative operations
    • Body sensor networks
  • Internet of Things
    • Communication technologies
    • Sensors
    • RFID
    • Printed electronics
    • Organic electronics
    • Physical layer mathematical operations

Schedule

Requirements

  • Each participant is required to attend and actively participate in the exercises.
  • Oral examination at the end of the semester

Reading List

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