Sensor Networks

Lecturer: Prof. Dr. Pedro José Marrón, Exercises: Songwei Fu

This lecture describes the fundamental concepts of sensor networks and how they differ from traditional networked systems that do not take energy and resource constraints into account. During the experiments, the students will deal with real-world deployments of sensor networks and use real sensor nodes to understand better the effects of real-world phenomena in aspects like link quality, localization, etc.

Place and Time (Updated):

  • Place (Updated):  SA-126 (Lecture and Exercises)
  • Lecture: weekly Wednesday 10:00-12:15 s.t. 
  • Exercises (Updated): biweekly Thursday  15:00 - 16:00 s.t.

The first lecture is held on April 19th 2017; the first exercises on April 20th.

Entry in LSF: Lecture und Exercise

More information can be found on our Moodle2 page. The password will be announced in the first lecture and in the exercises.

Programmieren A / B

Lecturer: Prof. Dr. Pedro José Marrón, Exercises: Ngewi Fet, Sascha Jungen

In dieser Vorlesung werden grundlegende Programmiertechniken in einer objektorientierten, modernen Programmiersprache (Java) besprochen.
Inhalte im Einzelnen:

  • Einführung und grundlegende Struktur von Programmen
  • Lexikalische Elemente, Datentypen und Variablen, Ausdrücke und Anweisungen
  • Objektorientierte Programmierung: Klassen, Methoden, Vererbung, Interfaces, Abstrakte Klassen
  • Standard und Utilityklassen
  • Generische Datentypen – Anwendung von Standardtypen
  • Ausnahmebehandlung
  • Ein- und Ausgabe mittels Streams
  • Graphische Oberflächen - Einführung
  • Ereignisbehandlung
  • Anwendung der JDK Utility Programme (Javadoc etc.)

Die Übungen sollen die Studierenden anregen die in der Vorlesung gelernten theoretischen Konzepte praktisch anzuwenden. Dabei werden grundlegende Programmierkenntnisse erworben und die Studierenden in die Lage versetzt einfache Programmieraufgaben selbstständig zu bearbeiten. Zusätzlich zu den Übungen werden Tutorien angeboten, welche Studirende mit besonderem Lernbedarf weiter unterstützen und die Inhalte der Vorlesung frühzeitig wiederholen. 

Zeit und Ort:

  • Ort:  SH 601 (Vorlesung), R14 R02 B07(Übung), A-003 und A-009 (Testate)
  • Vorlesung: wöchentlich Freitags 8:00-12:15 s.t. 
  • Übung: wöchentlich Dienstags  8:00- 10:00 s.t.
  • Testate: wöchentlich Montags 14:00- 16:00 s.t. und wöchentlich Dienstags 10:00- 12:00 s.t.

Die erste Vorlesung findet am 21.4.2014 statt, die erste Übung  02.05.2017, das erste Testat am 08.05.2017. 

Eintrag in LSF: Programmierung A, Programmierung B, und Übung A, Übung B, and Testate

Weitere Informationen finden Sie auf der Moodle2 page. Das Passwort wird in der ersten Vorlesung und in den Übungen bekannt gegeben.  

Case Study: Location-based Services

Lecturer: Dr. Marcus Handte

This case study covers fundamental concepts related to the development of location-based services from a theoretical and practical perspective. During the first half of the semester, basic models, algorithms, data structures and applications are introduced in a series of lectures with associated programming exercises. During the second half of the semester, participants will be designing and prototyping a location-based service for mobile (Android) devices.

The theoretical part of the case study covers the following contents:

  • Geometric, symbolic and hybrid location models 
  • Localization systems and algorithms for outdoor and indoor environments
  • (Energy-)efficient location acquisition and communication
  • Server-based and server-less location data management
  • Security and privacy aspects related to location information
  • Example location-based services and applications

The case study (4SWS) is suitable for participants at the Master level. Grading is based on the practical programming work during the semester and an oral exam at the end of the semester.  Depending on the participants, the course can be held either in English or in German. The lecture part of the course will take place Thursdays from 9.00h to 11.00h in SA-126. The kickoff takes place on Thursday, April 20th in SA-126. Participation during the kickoff meeting is mandatory. To access the materials (slides, papers, etc.) of the course and to get important notifications, please subscribe to the Moodle page of the course. 

Entry in LSF: Case-Study

Wireless Sensor Network Seminar

Tutor: Dr. Matteo Ceriotti

Computing and communicating devices become smaller and smaller; they moved from desks to everybody’s pocket; ultimately, they become embedded in the environment that surrounds our everyday life. This vision has been addressed under different names, Wireless Sensor Networks (WSNs) being one of them. As this happens, we become capable of monitoring in real-time the evolution of complex physical phenomena, as well as observing and controlling composite industrial processes. We can also instrument objects and scenarios to understand the current situation and smartly react to it. Unfortunately, the complexity of these systems, the limited visibility in system behaviour and the constrained available resources make the design and realisation of reliable systems challenging. 

This seminar aims at familiarizing students with important research topics in this field. The covered topics include, among others, routing, localization, sensing, communication, simulation, modelling, programming abstractions, applications and systems of low-power wireless embedded networks. Participants will have to do a literature research and they will have to create a high quality written report. Furthermore, they will have to give an oral presentation of their topics.

This seminar is suitable for students at the bachelor and master level. However, it cannot be chosen by master AI-SE students. This seminar is given in English. Please also note that the maximum number of participants is limited. If you have questions regarding this seminar, please send an email to

Entry in LSF: Seminar

The kickoff meeting for this seminar will take place on Thursday, 20.04.2017 between 13.00h and 14.00h in Room S-A 126.  This date is still tentative, please check this information for updates or send an email to to be notified about changes. Participation in this meeting is mandatory. 

Wireless Sensor Network Application Development Project

Tutor: Dr. Matteo Ceriotti

Wireless Sensor Networks (WSNs) have been widely deployed in many application domains including environmental monitoring, surveillance, healthcare, automation control and more. A typical WSN consists of a set of low-powered and inexpensive embedded sensor devices with specific sensing modalities and with computation as well as communication capabilities. These devices collaborate with each other by exchanging data through energy-efficient, short-range radios. The application provides its services by manipulating the sensory data collected by the deployed WSN.

In this project, you will learn how to develop an integrated application providing services by making use of a WSN. The topics that will be covered include:

  • Wireless sensor system programming
  • Sensory data collection
  • Data delivery and communication through IEEE 802.15.4 networks
  • Interfacing between the user and the deployed WSN 

This course will be taught in English. If you are not sure whether you fulfill the requirements or if you want to participate in the project, please send an email to

The kickoff meeting for this project will take place on Thursday, 20.04.2017 between 14.00h and 15.00h in Room S-A 126. This date is still tentative, please check this information for updates or send an email to to be notified about changes. Participation in this meeting is mandatory.

Entry in LSF: Bachelor and Master.

Moodle page

Unmanned middle-size Ground Robots (UGRs) (Project Group)

Tutor: Eduardo Ferrera

Nowadays, mobile robots are used in many applications, such as rescue missions, surveillance or people assistance. In these applications, robots usually need to operate in unknown environments, so they need to obtain information with their sensors and take intelligent decisions. In general, they proceed in a loop with several steps: 

  1. Information is obtained with the sensors on board the robot.
  2. Given the current information the best decision is made.
  3. The decision is carried out by the robot autonomously.

Mainly, mobile robots need to know where they are located and how to navigate safely to other places. For that, they have to use external sensors (e.g., GPS, compass, laser, etc.), plan trajectories, avoid obstacles, etc.

This project group is divided in three parts:

- Between middle April and early June a weekly meeting will take place. On it, the necessary theoretical background in robotics will be taught (history of robotics, types of robots, how to make them navigate...)

- Between middle April and early June a second weekly meeting will take place. On it, the necessary background of ROS (the Robotic Operating System) will be taught (topics, messages, parameters...)

- From early June to end of July the knowledge acquired will be used to build and make navigate a fully functional robot.

This project group is only suitable for AI-SE master students and it will be taught in English. A fluent knowledge of C/C++ will be also required. If you want to participate in this project or for further information, please contact Eduardo Ferrera (

The kickoff meeting for this seminar will take place in Room S-A 126, from 14:00h to 16:00h, on Tuesday, April 18th, 2017. It is mandatory to attend this meeting in order to participate in the project group. 

Entry in LSF: Project Group  

Augmented Reality Navigation Project and Seminar (Bachelor Project/Seminar)

 Tutor: Marcus Handte 

With their broad variety of sensors and their ability to render 3D models in real time, modern smart phones are an interesting platform to support augmented reality visualizations. In order to overlay a virtual 3D world on top of camera images of the physical world, it is necessary to properly capture the user’s orientation using the sensors built into the device and to adjust the model accordingly.

In this project, the participants will develop a navigation application for Android devices that leverages OpenStreetMap data to route the user to a configurable destination. In addition to the widely used map-based visualization, the application will include an augmented reality visualization that overlays the remaining route on top of a video generated by the device’s camera. An (optional) associated seminar  will cover AR-related research issues including localization, sensor management and visualization. While developing the application in the project, participants will have to work with the sensor framework provided by Android and they will have to learn the basics of Open GL. 

This course will be held in German. The project and its associated seminar are suitable for students at the bachelor level. The number of participants in this project is limited. If you want to participate, please send an email to before March 13th, 2017. Later participation requests cannot be accepted since, due to several requests from students, the course already starts before the beginning of the lecture period.