iPraktikum Summer Semester 2025

Course description

In this onsite course, you develop mobile applications in the context of a larger system architecture. Depending on the project, you work with application servers, machine learning algorithms, smart sensors, intelligent clothing, wearables (like the Apple Watch), or microcontrollers.

You get to know workflows, activities and tools of state-of-the-art agile software engineering, in particular agile hardware/software co-development, from requirements engineering to system delivery. You learn Apple’s programming language Swift, UI frameworks such as SwiftUI, and modern paradigms for asynchronous programming. You gain hands-on knowledge in the fields of system modeling, usability engineering and continuous integration and delivery.

Industry partners provide real problem statements. You get real team and project experience while working tightly together with a real client towards a real deadline.

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

Bayerische Polizei

mASD replaces the Bavarian police’s paper-based towing workflow, which currently relies on handwritten forms and slow radio calls. The app allows officers to scan license plates, auto-retrieve vehicle and owner data, capture photos, measure distances on-site, and submit towing requests digitally with real-time status updates. The goal is faster, more accurate processing with less administrative overhead—though, in practice, it mainly streamlines documentation rather than changing the underlying decisions about when a vehicle gets towed.

Team members: Elisabeth Friesinger (Project Leader), Yassine Souissi (Coach), Erhan Varlik, Manuel Grabmayer Sarah Niggl, Simon Seehausen, Matteo Merz, David Unterlinner, Leon Beichter

Customers: Matthias Niessner, Matthias Knerr

BMW

BMW Vision XR rethinks how vehicle design reviews are conducted. Today, presenting car prototypes in XR requires expensive hardware setups and complex workflows — but must such a critical process be so cumbersome?

This application for Apple Vision Pro enables designers to load high-fidelity BMW models, place them naturally in customizable virtual environments, and inspect them with realistic lighting and shadowing — all using only the headset. It allows teams to alter surroundings, control interaction modes, and review designs anywhere, reducing hardware costs and setup time while making immersive design reviews more accessible and scalable

Team members: Lucas Brand, Alexander Plaikner, Thomas Biedermann, Mark Stockhauser, Kasper Kejser, Anastasiia Vershchagina, Polina Ultina, Josef Schmid (Coach), Maximilan Anzinger (Project Lead)

Customers: Gareth Rogers, Manish Mistry, Dr. Matthias Oberhauser

E.ON

FutureScape addresses a surprisingly old-fashioned problem: planning solar panels and EV charging is still done with sketches and paperwork, making it hard for homeowners to visualize real outcomes. This mixed-reality app for Apple Vision Pro lets users view 3D models of their buildings, automatically align them to real locations, and experiment with placing solar panels and charging stations in an intuitive spatial workspace. The result is clearer, faster energy planning—though ultimately, it still serves to convince customers to buy E.ON’s solution.

Team members: Tobias (Project Lead), Walid Baroudi (Coach), Ping-Yu Huang, Konstantin Starke, Matyas Vascak, Arlind Ismaili, Jakub Jakubczyk, Theresa Wilhelm

Customers: Christian Kemper, Linus Theissen, Carl-Hendrik Holthaus

iABG

EmARgency addresses the classic problem that 112 calls rely on incomplete, shouted descriptions under stress. The system splits the workflow across three apps: reporters on iPhone send structured info with photos/video; dispatchers on Vision Pro review, anonymize, and select what to forward; and response teams on iPad receive a clear briefing before arrival. The idea is faster, clearer communication. In practice, its value depends entirely on people actually using the app in emergencies instead of just calling.

Team members: Matthias Linhuber (Project Leader), Ali Taha (Coach), Catalina Schulz, Doruk Bildibay, Kevin Gruber, Lukas Kratzel, Sabrina Glatz, Troy Rivera Volkogon

Customers: Martin Glas, Levente Csik

Quartett

MatrixVision tackles a sales problem: modern cars have advanced lighting systems, but customers never actually see them in action, so the benefits feel abstract. The app lets buyers visualize a car in real environments through Vision Pro or iPad, and control headlights and driving scenarios using hand gestures. This makes the features more tangible and persuasive. In the end, though, it’s still a guided demo tool for convincing someone to buy a specific model, just with nicer visuals.

Team members: Ramona Eckert (Project Leader), Jonathan Parth (Coach), Altin Azizi, Erin Kerciku, Arlind Ismaili, Karl Freund, Ming Hai Nguyen, Sven Hanakam, Wan-Ting Chen

Customers: Leon von Tippelskirch, Nityananda Zbil

Schwarz IT

Navig-AR tackles the all-too-common “wander around the supermarket lost at 19:58” problem. Users create a grocery list on iOS, and the Vision Pro app guides them through the store using indoor positioning, beacons, and pathfinding over a store map. It highlights items in space and suggests the fastest route to checkout. The pitch is convenience and reduced frustration—though in practice it also reinforces the same recommendation and upselling dynamics stores already use, just in a shinier, spatial form.

Team members: Philipp Nagy (Project Leader), Anastasiia Iakovleva (Coach), Abhijeet Sutar, Leon Liang, Manuel Ploner, Marcos Oliva Kaczmarek, Simon Graeber, Simon Winter, Sophie Kutter

Customers: Benjamin Mannich, Felix Sawo

Siemens

SafeGuard addresses a real issue: factory safety training is usually abstract, outdated, and not connected to the physical environment where accidents happen. The system uses an iPad to map machines and hazard zones, and a Vision Pro headset to display real-time alerts, spatial danger markers, and wrist-based instructions directly where the worker is standing. It can also detect falls and log incident reports. The idea is to make safety guidance immediate and actionable — though it relies heavily on workers actually wearing a headset on the shop floor.

Team members: Patrick Bassner (Project Leader), Fangxing Liu (Coach), Senan Aslan, Maia Filip, Jannis Höferlin, Nayer Kotry, Catherine Liang, Vasily Sizykh, Jennifer Wagner

Customers: Jochen Nickles, Dr. Jan Philip Bernius

TUM

TUMi is a chatbot designed to fix a familiar university problem: too many programs, too many pages, and no clear way to find what matters. It answers common questions instantly, recommends suitable programs based on user goals, and can send documents or registration links directly in chat. The team also gains analytics to understand what people are asking. It’s a sensible improvement — though in practice it mostly replaces a cluttered website with a friendlier interface, not a fundamentally new interaction model.

Team members: Felix Dietrich (Team Lead), Arbina Shaba (Coach), Sofia Loukianova, Gabriel Salapic, Oscar Harle, Steffen Schoel, Fuat Sebkan,

Customers: Silvia Hagn, Patrick Lenz, Lisa Wintersberg