Today, Prof. Paul Grünbacher of JKU gave a speech in the colloquium of the computer science department. The topic was monitoring requirements at run-time in systems of systems, see our announcement. Thank you, Paul, for teaching us! Below, please find some photo impressions.
Team / Project Cognimaster reports:
In cooperation with the industry partner, Knowis AG, the team 9 of the AMOS project developed a product called “Cognimaster”. It is a cognitive service based web application, providing insights on unstructured (big) data from social media and news in order to obtain the Credit profile of a company.
Tapping into the newest technology of cognitive computing, the team used the Artificial intelligence technology from IBM (a.k.a. “Watson”) to explore the possibilities to aid decision-making in the financial sector. The application can be used to research any middle to large companies, taking into account the customers’ feedback on the companies and / or their products both directly from the customers, using twitter social network, and indirectly, using news articles available on the web. The cognitive services perform natural language analysis to define “sentiment” (positive or negative “mood”) of the text.
The main value of the product is that the customer feedback loop is shortened dramatically in comparison with the time, when the structured data starts “feeling” the impact of the customer feedback on the recent product launch or company – related news.
As the technology is still young, there is room for improvement of the unstructured data analysis results. With further development of this technology in future, highly precise big data analysis results will be available at any moment of time, revolutionizing managerial decision-making in not only financial industry, but many others as well.
Key words: cognitive computing, Watson, IBM cognitive services, artificial intelligence, credit profile, big data.
Team / Project Conference App reports:
As part of the lecture AMOS we developed an App to organize conferences.
The App allows the organizer to create and update events and track the number of participants.
The participants are able to use the App to register for events, receive the agenda and additional information, participate in Live Voting or give feedback for an event.
|Our Industry Partner||As leading service provider for IT Transformations in the German market Senacor accompanies enterprises from planning till realization.|
Our team consisted of two Product Owner: Marina Kurbanova and Katharina Grasser and five Software Developer: Clemens Hübner, Murad Isayev, Luong Trung, Najm Askri and Sonia Hidri.
In summary our team consists of students from 5 different countries which made team work very interesting and instructive – a very good experience.
Team / Project Rogue Vision reports:
Students of the Agile Methods Open Source Project teamed up with Siemens Corporate Technology to develop Rogue Vision, an Open Source Industry 4.0 Data Analytics Application. The App enables remote monitoring of the Siemens flexible transportation line Demonstrator.
The Demonstrator was developed by Siemens AG together with Festo, SAP and Deutsche Telekom as an Industry 4.0 research project for the IT-Gipfel 2015 event in Berlin. Core of this Demonstrator is a flexible transportation system with so called Carriers as production containers that can be tracked and controlled individually on the production line.
The software system that was developed by the FAU Students is able to identify and visualize the energy consumption and the position of the Carriers on their way through the production line. As a result, it is possible to see different types of Carrier contamination types that are based on increased energy consumption of the Carriers. Additionally, Rogue Vision has possibilities to display the flexibility of the Demonstrator line by visualizing the Carrier speeds of the individual Carriers. The goal is to possibly integrate these functionalities into the production environment to detect Carrier Contamination or issues on the Demonstrator in real time.
For further information and technological details please check out the project wiki.
Team / Project CAODIC reports:
CAODIC – Collision Avoidance using Object Detection and Inter-car Communication
As part of the course AMOS (Agile Methoden und Open Source), Team 5 developed a program for object detection and inter-car communication.
Team / Projects DoIP Wireshark Plugin reports:
|Topic||DoIP Wireshark Plugin|
|Team Members||Tobias Ibler, Waqas Hasan, Sebastian Schinabeck, Dustin Nguyen, Michael Körber|
|Industry Partner||AVL DITEST GmbH|
As cars depend more and more on IT, the currently used and outdated CAN Bus needs to be replaced by a newer technology: Ethernet. Therefore, DoIP (Diagnostic communication over Internet Protocol – ISO-norm 13400-2:2012(E)) has been developed. It’s a protocol layer on top of UDP/TCP and serves the main goal of sending diagnostic information. Nowadays, only few cars use this technology, but in the future there will be a rapidly growing number of cars supporting DoIP communication.
On this account, the AMOS-project with our industry partner AVL DITEST GmbH was about developing a Wireshark Plugin that helps to read the DoIP protocol easily. Therefore, the Plugin analyzes and visualizes DoIP messages sent between a Tester and the car’s ECUs according to the ISO-norm.
Wireshark is a cross-platform network protocol analyzer. It lets you capture and interactively browse the traffic running on a computer network. Wireshark is freely available and released under GNU General Public License version 2.
After 13 weeks of hard project work using an agile approach, we have been able to finish our project on time and demonstrated the Plugin on the AMOS Demo Day on July 13, 2016. Even though we suffered three students leaving the project team early, we consider our outcome as huge success.
Finally, we would like to thank our industry partner AVL DITEST GmbH for the great collaboration and Prof. Riehle’s team for the support during the project.
For further information, please check out our project repository.
Team / Project MORFeus reports:
Our project, the Mobile Robot Framework, was conducted in cooperation with the Develop Group. Our objective was to build a mobile, platform independent framework that would allow interaction and communication with the robot provided by the Develop Group. We lovingly named the robot MORFeus. Our team consisted of 6 computer science graduate students and one international information systems graduate student. All of us were highly motivated to work on this project. The atmosphere in the group was outstanding and all the team members bonded astoundingly well over the course of the project. This and our high qualification lead to a result that exceeded the expectations of our supervisor and our industry partner and ourselves.
Although it was a challenge finding into the Scrum process, our team meetings became succeedingly productive and professional as we got used to each other. A highlight of every sprint-meeting was experiencing the new functionalities that our robot and framework could perform every week. The constant improvement in our software defiantly helped to keep hopes high and tempers low. Every milestone in our project felt like a great achievement that we had reached together. And only through our teamwork could we overcome the numerous challenges that stood in our way. The difficult implementation of the camera stream (which caused several sleepless nights), the reworking of the collision sensors and finally the integration of joystick controls were no small feats, but we accomplished them together.
All of us are glad that we participated in this project together. It was a lot of work and dedication that we put into this project, but while we drive around MORFeus and see other people interact with the framework we built, we all agree that it was worth it.
Team: Markus, Florian, Andreas, Jan, Maximilian, Valerie, MORFeus, Martin and our industry partners
Team / Project BLEaring reports:
We worked on an evaluation project together with Sivantos (former Siemens Audiology). The topic was the development of a medical health care App allowing monitoring and controlling bluetooth low energy (BLE) hearing aids from a smartphone. Many approachyes, frameworks and libraries were evaluated and in the end we set up a project architecture and a smoothly working library ecosystem, all documented on our project page.
The following key features were successfully evaluated and implemented:
- BLE support for multiple connections at the same time
- iOS and Android support
- A themable UI
- A UI-Tour
- A Graph for displaying measurements transmitted via BLE in real-time
Abstract: This thesis examines the power of modern NoSQL systems in conjunction with WOM to analyse and manage the article’s data of Wikipedia. The Wiki Object Model (WOM) is a machine readable semi-structured representation of markup produced by different wiki engines. The systems studied are native XML databases (Sedna, BaseX, eXist-db, X-Hive, Oracle Berkley DB XML and Apache Xindice), XML-enabled databases (PostgrSQL, MySQL, MariaDB), JSON-based document stores (Couchbase Server, MongoDB), Wide Column Stores (Apache HBase) and multi model databases (ArangoDB, OrientDB). As a foundation for the further analysis of suitability the analytical database’s expected data volume, query profile and workload is investigated. Subsequently, the listed systems are evaluated regarding to their functional and non-functional suitability for the given use case. The functional part is derived by the system’s capability of executing the given query profile – query driven schema design. The non-functional part is dictated by the amount of data which needs to be processed, and the expected workload. The list of potential system candidates is narrowed down to two whose resource consumption and functional suitability for the given use-case is described in further detail. The proposed research is the technical foundation for choosing and deploying the first prototype of an analytical database unlocking the structured data of Wikipedia.
Keywords: Wikipedia analysis, big data, NoSQL, Sweble
PDFs: Master Thesis
Reference: Patrick Kaltenmaier. Wikipedia in times of BigData – Einsatz von NoSQL-Systemen zur Verwaltung und Analyse von Wikipediainhalten. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2016.
Abstract: Wahlzeit is a photo sharing and rating web application used for teaching at FAU. This thesis defines an API to Wahlzeit as a headless service which provides all necessary information to accommodate a wide array of possible clients. To achieve this, the design decisions to be made when connecting clients to the service are analysed and a resulting design is defined. Appropriate technology is chosen for its implementation and the existing code-base is adjusted accordingly. As a proof of concept, an Android mobile client is implemented to interact with the service.
Keywords: Wahlzeit, ADAP, REST-API, Android
Reference: Iordanis Kosoglou. Design and Implementation of a Multi-Client API for Wahlzeit. Master Thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg: 2016.