700.320 (20W) Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems

Wintersemester 2020/21

Registration deadline has expired.

First course session
07.10.2020 16:00 - 18:00 Online Off Campus
... no further dates known

Overview

Due to the COVID-19 pandemic, it may be necessary to make changes to courses and examinations at short notice (e.g. cancellation of attendance-based courses and switching to online examinations).

For further information regarding teaching on campus, please visit: https://www.aau.at/en/corona.
Lecturer
Course title german Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems
Type Lecture - Seminar (continuous assessment course )
Course model Online course
Hours per Week 2.0
ECTS credits 4.0
Registrations 10 (30 max.)
Organisational unit
Language of instruction English
Course begins on 07.10.2020
eLearning Go to Moodle course
Seniorstudium Liberale Yes

Time and place

Please note that the currently displayed dates may be subject to change due to COVID-19 measures.
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Course Information

Intended learning outcomes

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

Teaching methodology including the use of eLearning tools

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

Course content

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

Examination information

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.

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Subject: Informationstechnische Vertiefung (Compulsory elective)
      • 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)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • 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)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • 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)
    • Subject: Information and Communications Engineering: Supplements (NC, ASR) (Compulsory elective)
      • 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)
    • Subject: Technical Complements (NC, ASR) (Compulsory elective)
      • 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)

Equivalent courses for counting the examination attempts

Wintersemester 2023/24
  • 700.320 VS Seminar in Big Data, Predictive Analytics and Automation (2.0h / 4.0ECTS)
Wintersemester 2022/23
  • 700.320 VS Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h / 4.0ECTS)
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 2019/20
  • 700.320 VS Seminar on Big Data, Predictive Analytics, and Automation in Telecommunications and Intelligent Transportation Systems (2.0h / 4.0ECTS)