700.320 (19W) Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems

Wintersemester 2019/20

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Erster Termin der LV
16.10.2019 16:00 - 18:00 B04.2.210 Besprechungsraum IST Off Campus
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Überblick

Lehrende/r
LV-Titel englisch
Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems
LV-Art
Vorlesung-Seminar (prüfungsimmanente LV )
Semesterstunde/n
2.0
ECTS-Anrechnungspunkte
4.0
Anmeldungen
7 (30 max.)
Organisationseinheit
Unterrichtssprache
Englisch
LV-Beginn
16.10.2019
eLearning
zum Moodle-Kurs
Seniorstudium Liberale
Ja

Zeit und Ort

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LV-Beschreibung

Intendierte Lernergebnisse

At the end of the seminar, each student should have been confronted with the following aspects:

  • A brief overview of basic concepts of modern Telecommunications and/or Intelligent Transportation Systems
  • A brief overview of basic concepts with respect to Big Data, Analytics, and Machine Learning
  • A detailed view of a selected topic supported by one or more papers from the relevant literature. See list of selected topics

Lehrmethodik inkl. Einsatz von eLearning-Tools

This Seminar lecture trains the students in an extensive independent research-oriented coached self-learning.

Inhalt/e

Selected Topics, just for illustration:

A) Telecommunications Systems

  • Big Data in Telecommunication Operators: Data, Platform and Practices
  • Big Data Analytics, Machine Learning, and Artificial Intelligence in Next-Generation Wireless Networks
  • Big Data-Driven Optimization for Mobile Networks toward 5G
  • Big Data Driven Hidden Markov Model Based Individual Mobility Prediction at Points of Interest 
  • A Survey for Mobility Big Data Analytics for Geolocation Prediction
  • Smartbuddy: Defining Human Behaviors Using Big Data Analytics in Social Internet of Things
  • Use cases and challenges in telecom big data analytics 

B) Intelligent Transportation Systems

  • Big Data Analytics Architecture for Real-Time Traffic Control
  • Big Data Analytics in Intelligent Transportation Systems: A Survey
  • Big Data for Social Transportation
  • Big Data Driven Vehicular Networks
  • Intelligent Method for Identifying Driving Risk Based on V2V Multisource Big Data
  • Data-Driven Prediction System of DynamicPeople-Flow in Large Urban Network Using Cellular Probe Data
  • Data-Driven Reinforcement Learning–BasedReal-Time Energy Management System for Plug-In Hybrid Electric Vehicles
  • Urban Transportation System Analytics And Optimization: A Sensor Data-Driven Approach
  • Smart cities with big data: Reference models, challenges, and considerations

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.

Prüfungsmethode/n

Presentations

Final exam

Prüfungsinhalt/e

Selected papers

Presentations' slides

Lecture slides

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Fach: Informationstechnische Vertiefung (Wahlfach)
      • 10a.3 Wahl von Lehrveranstaltungen ( 0.0h VO/VC/KS/UE / 6.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 4) ( 0.0h VK, VO, KU / 14.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR) (Wahlfach)
      • Wahl aus dem LV-Katalog (Anhang 5) ( 0.0h VK, VO, KU / 12.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technische Ergänzung I (Pflichtfach)
      • 2.1-2.2 Vorlesung mit Kurs oder Vorlesung mit Seminar ( 4.0h VK/VS / 8.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)
  • Masterstudium Information Technology (SKZ: 489, Version: 06W.3)
    • Fach: Technische Ergänzung II (Pflichtfach)
      • 3.1-3.3 Vorlesung mit Kurs oder Vorlesung mit Seminar ( 6.0h VK/VS / 12.0 ECTS)
        • 700.320 Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h VS / 4.0 ECTS)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Wintersemester 2021/22
  • 700.320 VS Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h / 4.0ECTS)
Wintersemester 2020/21
  • 700.320 VS Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h / 4.0ECTS)