Category Archives: 3.3.2.1 AMOS Projects

Show-casing the 2017 AMOS project “Simulating a car’s ECUs using a Raspberry Pi”

Project name Simulating a car’s ECUs using a Raspberry Pi
Project mission The mission of the project is to implement a scriptable Electronic Control Unit simulation environment that can siumlate diagnostic communication. Diagnostic Developers can model the diagnostic behaviour of single ECUs or whole cars inside a box such a Rasperry Pi. The communication protocol used in the vehicle diagnostic is Unified Diagnostic Services. It is a Request-Response Protocol. The ECU provides Services which can be called by the client. The mission of this particular project (in the context of the product vision).
Industry partner AVL DiTest
Team logo
Project summary Our task was to simulate ECUs from a car via Raspberry Pi. For the communication, the ECUs in a car are connected via CAN-Bus. We used the UDS-protocol for the communication of the ECUs. Which functions from the ECUs are supported is defined in the lua file. An example: If you are reading the name of the ECU, each lua file (ECU) should send another name back, e.g. engine, airbag… Because each ECU has a different task in in the car, all the definitions within the different lua files are different. Due to the fact that the Raspberry Pi is loading several lua files at the same time, a behaviour like in the car is simulated, because several ECUs are communicating with each other.
Project illustration
Project repository https://github.com/christian-reintges/amos-ss17-proj4

Show-casing the 2017 AMOS project “Raspberry Pi as user control board for multimedia evaluation boards”

Project name Raspberry Pi as user control board for multimedia evaluation boards
Project mission The mission of our project is to enhance the Sivantos Fitting Software System with a Raspberry Pi user control board to test the software efficiently and rapidly replacing the existing manual interaction with the system under test. Our project enables test engineers and manual testers at Sivantos to test their software faster, more comfortably, more efficiently and more thoroughly. By enabling one of the world’s leading manufacturers for hearing aids to increase the safety of their products, we provide value to patients suffering from hearing loss all around the world.
Industry partner Sivantos
Team logo
Project summary At first, we were not quite sure what our project was about. The subject was quite abstract and we had few experience with the hardware. The first sprints were needed to get familiar with the development environment, the hardware components and the protocols needed to talk to the RaspberryPi.
As soon as we got familiar with all the components, we were able to implement more actual features. Testing was a bottleneck, as we had to test the soft-/ hardware interaction but only had two fully functional breadboards. The close cooperation with our industry partner was helpful not only for defining the scope of the project and prioritize features, but also for debugging hardware related problems. We learned a lot, not only about software development in unknown terrain but also about Scrum in general and the importance of interaction and communication within the team in particular.
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Team photo
Project repository https://github.com/varj888/amos-ss17-projSivantos

Show-casing the 2017 AMOS project “A factory simulation game for software testing and operator training”

Project name A factory simulation game for software testing and operator training
Project mission The mission of this 2017 AMOS project was to create a factory simulation in the style of a game. The core functionality should be the visualization of factory interior with all its machines and product flows. The elements should interact and at the end one should be able to retrieve statistics to improve the production process.
Industry partner Weber Maschinenbau GmbH, represented by Nuveon GmbH
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Project summary At the beginning of the semester, our customer Christoph Sauer from the software development company Nuveon gave us an introduction to the topic. The project started with two product owners and seven developers. By the end of sprint #4 there were three developers left. In 13 sprints we accomplished 38 user stories and released 10 official versions of our software. The product was implemented as a web application and from sprint #8 on our customer provided a server with public access for better manual testing (by the product owners and the customer). The final project release of the software provides basic administration and gameplay features. At the demo day our two customers confirmed that they are planning to extended it at Nuveon and/or another AMOS project.
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Project repository https://github.com/PrinzKarneval/amos-ss17-proj5

Show-casing the 2017 AMOS project “Virtual Ledger”

Project name Virtual Ledger
Project mission The mission of this 2017 AMOS project is to create a banking app that represents the product vision of the Adorsys banking app. The Adorsys banking app will have a multiple accounts feature. This allows the user to add and delete all existing bank accounts he or she has in a simple way. With one click he can overview his overall financial status and the balance for every single account. Furthermore, he can get access to all the transactions that happen within the bank accounts. In this way the application ensures that the user has full view over every bank account and every transaction in one single app. As special features the user will be able to create virtual saving accounts for his own purpose and manage this accounts together with other users, so that he can achieve his saving goals with the help of an intelligent algorithm that transfers constantly money to the saving account.
Industry partner adorsys
Team logo
Project summary The Virtual Ledger App is capable of storing different bank accesses – and therefore accounts- from different banking institutions. So that a user can manage his or her accesses through one application. Furthermore, past transactions from one or several bank accounts can be shown – ranging from 4 weeks to 1 year or an user defined time span. In addition, in the calendar overview one month per page is shown and the balance for each date is accessible. Specific transactions of a date can be seen through clicking on it. Moreover, the app allows registered users to add friends to a contact screen and share a common saving goal with them . These saving goals can be specified for any future goal with or without other contacts. Additionally, the user can assign each saving goal several bank accounts.
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Team photo
Project repository https://github.com/BankingBoys/amos-ss17-proj7

Show-casing the 2017 AMOS project “Alexa, your personal financial Assistant”

Project name Alexa, your personal financial Assistant
Project mission The mission of this 2017 AMOS project is to create minimum viable product (MVP) for Alexa with the financial extension. Core functionality will be to check bank account information like the balance, transactions, or the credit limits. Manage transactions, pay bills, manage spending habits grouped in categories, all through a secure communication are features that will be included in the MVP. Additional functionality like a smart financial component will be added to the product if the time permits.
Industry partner Senacor
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Project summary In a team of 2 product owners and 6 software developers we developed a personal financial assistant using amazon’s speech recognition hardware, alexa. Our implemented skill, is able to support the customers in their daily financial activities. Using speech, the customer is able to get information about the bank account status, transactions, stock shares and more. Furthermore, the customer can easily pay bills, send money to friends or create a savings plan. Our skill provides a tool to manage expenses in various categories like: auto, health or lifestyle, offering our customers an easy solution to track their spendings.
Project illustration
Project repository https://github.com/c-i-ber/amos-ss17-alexa.git

The 2017 AMOS Projects Line-up

We proudly present the initial set of confirmed AMOS projects for the upcoming summer semester. All projects will be developed as open source software on Github. Please register on StudOn, if you haven’t done so already, to learn more about the projects and make sure get you a seat in the class.

Table of contents

  1. Augmented reality robot (with Develop Group)
  2. Raspberry Pi as user agent (with Sivantos)
  3. Alexa, your personal financial assistant (with Senacor)
  4. Raspberry Pi as a simulated car (with AVL DiTest)
  5. Factory simulation (with Weber Maschinenbau)
  6. Gradle cloud deployer (with QAware)
  7. Virtual account ledger (with Adorsys)
  8. Icinga mobile app (with Netways)

Continue reading The 2017 AMOS Projects Line-up

The AMOS 2016 Project Show Case: Cognimaster

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.

The AMOS 2016 Project Show Case: Conference App

Team / Project Conference App reports:


Our Vision 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 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.

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The 2016 AMOS Project Show Case: Rogue Vision

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.

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The 2016 AMOS Project Show Case: CAODIC

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.

Summary The project implements a scenario needed for autonomous driving with the help of software agents: A bus stops at a bus stop vis-à-vis to a school. A car that drives behind the bus cannot see the children/humans starting to run across the street in front of the bus. Another car on the other side of the street detects the children and is able to warn the first car.
Overview
Main tasks
  • Integration and implementation of a simple bus/car and human detection algorithm
  • Integration of a software agent library
  • Implementation of the scenario using software agents and inter-process communication
Details The project involved developing a prototype that demos two communicating, virtualized hosts. Each host represents a car and one host (the client) warns the other (the server) about humans standing in front of a car/bus. The program reads and decompresses the video data and performs the {car,human}-detection for each frame. If the program detects a human standing in front of a car, a warning message is sent from the client to the server.
Setup
  • Operating System: Linux Ubuntu 14.04
  • SW Agents Library: C++ Actor Framework (CAF)
  • Object Detection Library: OpenCV
  • Messaging Format: HDF5, Google Protobuf
  • Deployment: Docker, Travis and Jenkins
  • Virtualization: Docker
Industry partner Continental AG, Regensburg
Coach Prof. Dr. Dirk Riehle
Team members Richard Fuchs, Daniel Götz, Nils Häusler, Jonas Heinrich, Elisabeth Hoppe, Leonard Keidel, Debin Liu
Outcome The following video shows the outcome of our project, including the {car,human}-detection, as well as the communication: