Results of the iPraktikum SS2019
(Bernd Bruegge, Dora Dzvonyar, Dominic Henze, Paul Schmiedmayer, July 2019)
Results of previous years
Goal
This lab course covers mobile applications for smart devices, ranging from standalone applications, embedded systems, including hardware and sensors to the design of modern interfaces for complex business applications. Students learn and apply software engineering and usability engineering techniques. This includes object-oriented modeling and system design, as well as the realization of graphical user interfaces, usability testing, continuous integration, and continuous delivery. Real industrial partners provided the problem statements and acted as clients. Twelve industry partners participated in the iPraktikum SS2019, each with a different problem statement and a separate team. More than 100 students delivered these applications using agile techniques and communicating continuously to their clients.
Program Management
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| Prof. Dr. Bernd Brügge | Dr. Dora Dzvonyar | Dominic Henze | Paul Schmiedmayer | Florian Bodlée |
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Organization
The chart shows the project-based organization of the course. All projects are shown as columns, including information about the customer, project management, and student team. A team of twelve student coaches dealt with the project management of the teams. Furthermore, cross-project teams with one member of each team (horizontal bars) dealt with different aspects during the project. The release management team was in charge of the right usage of version control, continuous integration, continuous delivery, and feedback management. The Usability Engineering team kept an eye on usability aspects and metrics of the mobile applications. The modeling team was responsible for the modeling activities, including the creation of informal models, i.e., trailer, mockups, and UML diagrams, to improve the communication of difficult aspects within the team.
Projects
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Project: B/S/H/ DataTr/ai/n is an app that helps with data collection for training machine learning models. BSH employees can be assigned to machine learning campaigns and participate in the data collection and image annotation. By uploading, annotating, and labeling images, required data can be collected, and with these data, the machine learning models can be trained. Team members: Prof. Dr. Bernd Brügge (Project Leader), Natalia Saiapova (Coach), Taylor Lei, Emil Oldenburg, Susanne Winkler, Borja Sánchez Clemente, Baris Sen Customers: Berkay Ogulcan Tutal, Yagiz Efe |
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Project: Gemeinde Kirchheim The SmartHeim2 mobile app helps the citizens of Kirchheim get realtime and historical information on the current traffic situation in their municipality and keeps them up-to-date on any impediments as well as giving them driving recommendations to avoid traffic. The SmartHeim2 web app enables traffic planners to simulate possible measures and try them out in advance. It also allows a comparison of current and historical data. Team members: Mariana Avezum (Project Leader), Ninah Nyaranga Wambugu (Coach), Patrick von Haller, Berzan Yildiz, David Schemm, Florian Schöttl, Nathalie Pett, Panarit Jahiri Customers: Tobias Schock, René Fassbender |
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Project: Goalplay Goalplay Video Coach helps amateur goalkeepers improve by providing them training programs, exercise tracking, and feedback. The goalkeepers can film their practice with a smartphone camera, and the app recognizes and logs their exercises in realtime. We use Apple ARKit for body & pose tracking, and a proprietary sequence model for classifying goalkeeper exercises. Team members: Dr. Juan Haladjian (Project Leader), Andi Turdiu (Coach), Andac Kürün, Kerkko Visuri, Yuwen Lu, Jonathan Mengedoht, Marie Schwahn, Sami Ibishi Customers: Cristian Prodaniuc, Samuel Roth |
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Project: iHaus In 2016, roughly 50% of elderly people above the age of 75 died after an accident at home. iHaus Lassie uses smart sensors and an innovative app to detect emergencies before they even happen – and act quickly if they do. Team members: Dominic Henze (Project Leader), Philipp Eichstetter (Coach), Kristian Klemon, Benedikt Vogler, Lukas Gerhardt, Yueze Zhang Customers: Ralf Pfleghar, Hamza Jrad |
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Project: MRI SHARP is a platform that helps patients with hand injuries in their postoperative care. The patient app shows instructional videos and provides realtime feedback using the smart glove. The therapist app helps therapists to track the progress of the patient and adjust the therapy accordingly. Overall, the project maximizes the benefits of postoperative therapy while preventing the potential further injuries. Team members: Nadine von Frankenberg und Ludwigsdorff (Project Leader), Victor Prüfer (Coach), Florian Kirchgeßner, Florian Hautmann, Jacqueline Bronger, Fouäd Samy, K. S., Melih Oezbeyli Customers: Dr. Kai Megerle |
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Project: MSG Traffic Light Aid (TLA) is an iOS app that helps to improve the driving experience of a driver. By predicting the behavior of every registered Traffic Light, TLA shows the driver the distance to the next Traffic Light and its current status, how long it stays green (or red), and recommends a speed. By following this recommended speed, the driver will always catch the approaching Traffic Light at a green light. TLA helps the driver avoid braking heavily to stop and drive in a safer and more eco-friendly way. Team members: Jan Philip Bernius (Project Leader), Ngoc-Minh Tran (Coach), Jonas Petry, Linus Michel, Lanyingzhu Luo, Paul Moosbrugger, Zhiquan Wang Customers: Oliver Feldmann, Jiong Yin |
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Project: NeuPro YAMA is a system designed to support workers in the process of maintaining boats. By controlling a robotic arm with an iOS application, YAMA greatly reduces the health risks associated with the manual work currently required to clean and repair yachts, as the workers are no longer exposed to toxic chemicals. By scanning the surface with a 3D camera, the system recognizes the boat hull's material and areas that need cleaning or repair. From the collected data, a path is calculated for the robotic arm to follow, while the worker has the possibility to control the workflow from the iOS application. Team members: Sajjad Taheritanjani (Project Leader), Anna Kovaleva (Coach), Maria Potzner, Felix Jedrzejewski, Jonas Brokmeier, Janik Halbherr, Jonas Tomasini Customers: Thomas Neumaier |
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Project: Quartett Chargify helps owners of electric cars schedule charging based on their calendar and motion profile. The user can see the upcoming events, their route, and how long they might need to charge their car to reach an appointment. The app predicts missing or wrong locations and times of events using the user's frequently visited locations. Additionally, events that are not listed in the calendar are suggested based on the user's data. Team members: Sebastian Klepper (Project Leader), Florian Bodlée (Project Leader), Yannick Spreen (Coach), Li Nguyen, Moritz Sternemann, Marlene Pfänder, Ebru Sözbir, Mauricio Garrido Customers: Christoph Bruns, Leon von Tippelskirch, Jonas Reimers |
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Project: Siemens IOT SiJ is an app that helps Siemens employees manage the loT machines on their shop floors. Our app allows employees to look up the machines available on the current network by scanning them. The data characteristics of the machines can then be displayed on a fully customizable dashboard. Additionally, by making use of ARKit on iOS devices, SiJ can produce an augmented reality experience to make the controlling and supervising of machine data a more immersive experience. Dashboards created by one employee can then be shared and used by other employees. Team members: Dr. Lukas Alperowitz (Project Leader), Alexandros Tsakpinis (Coach), Raymond Pinto, Łukasz Zalewski, Maoying Yang, Felix Elfering, Qingyu Li, Simon Huber Customers: Jochen Nickles, Dr. Markus Sauer |
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Project: Siemens Mobile SieMajor is an iOS application that unlocks the potential of the user to create music in an innovative way. Utilizing data from the internal sensors, the touch-responsive surface, as well as the built-in augmented reality engine of the device, SieMajor enables the user to explore different ways of interaction to make music. Further, the app lets you connect to devices within the same network in order to compose music together in a group of up to seven musicians. Team members: Zardosht Hodaie (Project Leader), Anh Montag (Coach), Marsil Zakour, Lukas Schöbel, Julia Sommer, Giuseppe Valletta, Paul Hofbauer Customers: Dr. Asa MacWilliams |
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Project: Zeiss MED myCONVIVO is an app targeted at nurses, surgeons, and pathologists who look forward to working with the Zeiss CONVIVO during brain surgeries and want to be prepared for the future. The Zeiss CONVIVO is a revolutionary medical device that changes the workflow of brain surgeries. Our app uses modern technologies such as AR and learning theory concepts such as gamification to improve the learning experience and speed up the learning process. Users can familiarise themselves with CONVIVO and test their knowledge, leading to safer and better brain surgery. Team members: Dr. Dora Dzvonyar (Project Leader), Matthias Linhuber (Coach), Diana David, Kristina Mach, Sandesh Sharma, Eldi Cano, Michael Schmid, Ming Yin Chan Customers: Christopher Käsbach, Kay-Uwe Clemen |
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Project: Zeiss RMS APEER bridges the gap between researchers and developers. Anyone on the platform can share custom image processing tools with the public. These tools can then be easily combined with a few mouse clicks regardless of the programming language they were written in. The APEER app packages this functionality for the iPhone, allowing researchers to run image processing workflows with custom parameters, receive notifications on completion and share their results with the community. Team members: Paul Schmiedmayer (Project Leader), Henri Tyl Allgöwer (Coach), Aziz Marzouki, Patrick Koch, Jan Peter, Alexandra Gertsenshteyn, Anelia Petrova Customers: Dr. Bernhard Fichtl, Thomas Irmer |
