Pervasive Computing

Students learn the methods and technologies, making computer systems in everyday life possible. Typical challenges are about the autonomous adaptation to the environment, the efficient resource usage and the spontaneous communication. The focus lies on the understanding of the cooperation of hardware and software as well as on the practical implementation of digital signal processors and sensor networks.

Semester	Summer semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical supplementary subject I and II
Teacher	Prof. Gian Luca Foresti , Prof. Christian Micheloni, Claudio Piciarelli. Pervasive Computing Group, Institute of Networked and Embedded Systems
Type of lecture and number of credits	VK 2 SWS, 4 ECTS
Description	The lecture series will aim to introduce the techniques for developing advanced artificial vision based systems. From the early stages of image creation to the most advanced techniques for image and video interpretation the course will propose the state of the art algorithms for detecting objects and understanding their behaviours. A small amount of hours will be reserved to laboratory activities.
Topics	Architecture of an artificial vision systems Low-level processing (object segmentation, object detection, etc.) Mid-level processing (object recognition, object tracking, etc.) High-level processing (behaviour analysis, event detection, etc.) Network configuration MATLAB Lab
Keywords	Image analysis; computer vision; object detection and recognition; machine learning; video networks
Prior knowledge	Signal processing fundamentals;
Learning objective	Understand the fundamentals of image processing, object detection and object tracking. Implement basic algorithms in MATLAB
Recommended Literature	Gonzales, Woods. Digital Image Processing. Prentice Hall
Language	English
Related Lectures	Digital Signal Processors Lab; Fundamentals of Image Processing Lab
Recommended Lectures

[700.460] Sensor Networks

Semester	Summer semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical supplementary subject I and II
Teacher	Prof. Bernhard Rinner, Pervasive Computing Group, Institute of Networked and Embedded Systems
Type of lecture and number of credits	VK 2 SWS, 4 ECTS
Description	Due to the advances in electronics and (wireless) communication, the development of networks of low-cost, low-power, multi-functional sensors has received increasing attention. These sensor networks are a new type of networked, embedded computing systems and are expected to become a key technology for many pervasive computing applications. This lecture covers the fundamental concepts of sensor networks, including hard- and software architectures, networking aspects, power-awareness, security and sensor fusion. The lecture is complemented by student talks on selected, application-oriented topics. In a related lab course ("Pervasive Computing Lab"), students can get hands-on experience in developing sensor network applications.
Topics	1. Hardware Aspects 2. Software Aspects 3. MAC Protocols 4. Routing 5. Synchronization 6. Security and Privacy 7. Applications
Keywords	Sensor nodes; Wireless networking; Data fusion
Prior knowledge	Embedded systems; ad-hoc networking
Learning objective	Knowledge of the fundamental concepts and applications of sensor networks
Recommended Literature	Dargie, Poellabauer. Fundamentals of Wireless Sensor Networks: Theory and Practice
Language	English
Related Lectures	Pervasive Computing Digital Signal Processors Wireless Networking
Recommended Lectures	Pervasive Computing

[700.400] Pervasive Computing

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical supplementary subject I and II
Teacher	Prof. Bernhard Rinner, Pervasive Computing Group, Institute of Networked and Embedded Systems
Type of lecture and number of credits	VK 2 SWS, 4 ECTS
Description	Pervasive Computing focuses on the computing systems for supporting every day life. Based on the rapid progress in mobile communications, micro electronics, sensor technologies and human computer interaction, modern computer systems can nowadays be integrated into everyday objects.
Topics	1. Introduction 2. Spontaneous Networking 3. Localization 4. Identification 5. Context-Aware Computing 6. Sensor Networks 7. Wearable Computing 8. Middleware 9. Applications
Keywords	Ubiquitous Computing; Wireless Networking; Localization; Sensors
Prior knowledge
Learning objective	Knowledge of fundamental technologies and applications of pervasive computing
Recommended Literature	Hansmann et al. "Pervasive Computing", Springer, 2003 Poslad. "Ubiquitous Computing", Wiley 2009
Language	English
Related Lectures	Embedded Systems, Mobile Computing, Traffic Informatics, Multimedia Informatik
Recommended Lectures

[700.450] Digital Signal Processors

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical specialization "Embedded Communications and Signal Processing" Technical supplementary subject I and II
Teacher	Prof. Bernhard Rinner, Pervasive Computing Group, Institute of Networked and Embedded Systems
Type of lecture and number of credits	VK 2 SWS, 4 ECTS
Description	Digital signal processors (DSPs) can be found in many devices such as mobile phones, PDAs and digital cameras. Their fields of application are ubiquitous ranging from control and measurement to audio and video processing. This lecture deals with the concepts of modern digital signal processors. It covers main topics of micro processor architectures, focuses on the characteristic features of DSP and presents up-to-date processors and development methods for DSP systems. Various case studies are presented during this lecture. The lecture is complemented by a lab course.
Topics	1. Introduction to micro processors 2. From micro processors to DSPs 3. Development of DSP systems 4. Examples of DSPs 5. DSP programming 6. DSP applications and case studies
Keywords	Microprocessors; Data path; Memory Systems
Prior knowledge
Learning objective	Get an understanding of digital signal processors (DSPs) Features, architectures, systems and applications Programming and application development Overview of various DSPs
Recommended Literature
Language	English
Related Lectures	Rechnerorganisation Digitale Signalverarbeitung Signal Processing Architectures for Embedded Embedded Microcontroller Lab
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Courses and Labs [KU]

[700.401] Pervasive Computing

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical supplementary subject I and II
Recommended Semester
Teacher	Lukas Esterle, Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Lukas.Esterle@aau.at
Type of lecture and number of credits	KU 2 SWS, 3 ECTS
Description	This course is complimentary to Pervasive Computing VO and will give an introduction on programming sensor nodes and sensor networks. For this course, oracle sunspots will be used for demonstration and programming purposes. In multiple sessions, the students will learn to use different sensors from the sunspot and how to facilitate them to tackle different problem areas. This course is a mix of lab and presentations in which students prepare and program their own solutions and present their solution to the class. The course will be held blocked on certain dates. There will be a kick-off before every assignment to discuss the problem. The solution is prepared in small groups autonomously (no fixed lab sessions).
Topics	1. Introduction/Motivation 2. Introduction to Oracle SunSpots 3. Sensor network programming / Spontaneous networking 4. Localization 5. Identification
Keywords	sensor nodes, sensor networks, oracle sunspots
Prior knowledge	Programming in Java/C#
Learning objective	Students will learn how to program their own sensor nodes as well as entire networks of sensor nodes for a specific purpose. They will employ different sensor on a sensor node to implement a building monitoring system.
Recommended Literature	Java ist auch eine Insel; http://www.galileocomputing.de/openbook/javainsel7
Language	English
Related Lectures	Pervasive Computing, Sensor Networks (Lab and VO)
Recommended Lectures	Pervasive Computing, ESOP

[700.451] Digital Signal Processors

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical specialization "Embedded Communications and Signal Processing" Technical supplementary subject I and II
Recommended Semester
Teacher	Dipl.Ing. Bernhard Dieber, Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Bernhard.Dieber@aau.at
Type of lecture and number of credits	KU 2 SWS, 3 ECTS
Description	Digital signal processors (DSPs) can be found in many devices such as mobile phones, PDAs and digital cameras. Their fields of application are ubiquitous ranging from control and measurement to audio and video processing. This lecture is the complementary lab course to the DSP VK. From practical examples students learn to program a DSP in the C programming language as well as in assembler.
Topics	1. Introduction to DSP programming 2. Audio processing 3. Performance optimization and parallelization 4. Image processing 5. Image compression
Keywords
Prior knowledge	Basic knowledge in C and assembler programming as tought in Operating Systems and Computer Organization
Learning objective	Get an understanding how to program a DSP Application areas of digital signal processors Performance optimizations and assembler programming Optimization strategies in compilers
Recommended Literature
Language	English
Related Lectures	Programmieren in C/C++
Recommended Lectures

[700.461] Sensor Networks

Semester	Summer semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing" Technical supplementary subject I and II
Recommended Semester
Teacher	Dipl.Ing. Bernhard Dieber, Dipl.Ing. Lukas Esterle Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Bernhard.Dieber@aau.at, Lukas.Esterle@aau.at
Type of lecture and number of credits	KU 2 SWS, 3 ECTS
Description	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.
Topics	1. Sensors and sensor networking 2. Context awareness 3. Self-adaptation / Self-organisation
Keywords	Smart-office, Pervasive Computing
Prior knowledge	Programming
Learning objective	Pitch project ideas and present those ideas. Find fundamentals for own projects and how to extend the existing technology/solutions. Implement own idea in small group. Combine idea with other groups/projects.
Recommended Literature
Language	English
Related Lectures	Pervasive Computing VO, Sensor Networks VO
Recommended Lectures	ESOP

[700.482] ICT-Lab: Pervasive Computing

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical supplementary subject I and II
Recommended Semester
Teacher	Dipl.Ing. Melanie Schranz Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Melanie.Schranz@aau.at
Type of lecture and number of credits	KU 2 SWS, 3 ECTS
Description	The course Design of Digital Circuits, KU, which takes place as part of the bachelor studies Informationstechnik in summer semester, introduces basic concepts of digital circuit design and hardware description languages. In the lab part of this course, combinational and sequential hardware circuits are designed, implemented and simulated using VHDL with the help of the environments ModelSim and Quartus powered by Altera. A further step in hardware development is to synthesize and run the circuits using real hardware, which is the main topic of this lab-unit.
Topics	1. Register Design 2. Driving the PS/2 Keyboard and Visualization on the Altera DE2 Development and Education Board 3. Central Logic and ALU of a Calculator
Keywords	Logic gates, optimization, VHDL, sequential circuits
Prior knowledge	Understanding and applying basic concepts of programming in the hardware description language VHDL Understanding of combinatorial and sequential logic
Learning objective	Design, Implementation and synthesis of complex VHDL code on hardware
Recommended Literature	Mealy, Brian; Tappero, Fabrizio. Free Range VHDL, http://www.freerangefactory.org
Language	German/English
Related Lectures
Recommended Lectures	Entwurf digitaler Schaltungen (VO+KU)

Research Seminar and Project

[700.498] Research Seminar on Pervasive Computing

Semester	Summer semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing"
Recommended Semester
Teacher	Prof. Bernhard Rinner, Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Bernhard.Rinner@aau.at
Type of lecture and number of credits	SE 2 SWS, 6 ECTS
Description	In this research seminar topical subjects in the area of Pervasive Computing will be regarded. Based on topical scientific publications on a particular subject participants develop a powerpoint presentation and a paper on the selected topic, and finally give a talk for their fellow students and their supervisor. NOTE: The seminar will be held in blocks. Topics will be presented and assigned in the first meeting. Also the semester's schedule will be presented in the first meeting.
Topics
Keywords
Prior knowledge
Learning objective	improve their knowledge in a particular field. learn to read and interpret scientific publications. prepare a presentation by themselves. practice to give a presentation and to discuss with an audience.
Recommended Literature	Scientific Publications
Language	English
Related Lectures
Recommended Lectures

[700.496] Research Project in Pervasive Computing

Semester	Winter semester
Allocation in the Curriculum	Master Curriculum, Information Technology Technical specialization "Pervasive Computing"
Recommended Semester
Teacher	Prof. Bernhard Rinner, Pervasive Computing Group, Institute of Networked and Embedded Systems Email: Bernhard.Rinner@aau.at
Type of lecture and number of credits	KU 8 SWS, 12 ECTS
Description	Students work independently on a research oriented project.
Topics
Keywords
Prior knowledge
Learning objective
Recommended Literature
Language	English
Related Lectures
Recommended Lectures