Abstract: Cities are heating up during the summer, and deaths related to this are on the rise. To mitigate this ever-increasing risk, we have prototyped, built, and user-tested an entirely open-source, personalized city climate warning system called Wera. Wera can access the high-density temperature sensor network in Zurich, along with meteorological data and the user's location, to formulate a weather and risk potential report with Llama3, which is then synthesized into either German or English for the end user. Wera primarily targets seniors, as they are the most affected by the city's hotspots. It features a very intuitive and accessible interface, making it a reliable weather risk informer and a helpful weather assistant. Wera comes in two form factors: the Kub, its strengths being its constant visibility, personal feeling, and accessibility, and the Fong, which is widely deployable and offers the option to ask back questions directly on your phone.
Process & Context: This project began after examining Zurich's "Open Data Katalog," where we encountered a dataset associated with a city climate sensor network overseen by Meteoblue. Recognizing its untapped potential, we reached out to ZHAW, the project's originators, to discuss its utilization. They confirmed that the data had been largely overlooked.
In response, we created multiple versions of our devices: three versions of the Kub, one version of the Fong, and about nine major ones for the server, all developed using the Go programming language. The system's response prompts are dynamically generated, pulling from various real-time data sources, thereby bypassing the quite unreliable decision-making processes of large language models, and enhancing the system's robustness.
We tested a Kub prototype, equipped with a Raspberry Pi and a GPS sensor, with two elderly users to refine the user experience. Finally, we made the project's software, schematic diagrams, CAD files, and their accompanying documentation open source by publishing it on GitHub with an MIT license.
Prototypes
Sketches and CAD for Industrial Design
GitHub Page
Industrial Design
User Testing
Abstract: Neuranect is a user-friendly, evidence based therapy device for delaying dementia, employing serious games and a compact motion capture system, that allow users to control the games trough embodiment in order to train their cognitive and physical abilities. It is easy setup and provides adaptive gestures and control possibilities to ensure autonomy when playing games, accommodating various physical conditions and severity levels of dementia by keeping the startup process completely automated.
Process & Context: Our process kicked off through a deep dive into neuroplasticity, different stages of dementia, and the role of serious games in this area. To also validate the gathered information we contacted multiple neurologists and serious game experts. We then went over to field research, and spoke to different retirement homes to then interview the people working and living there. We formed our idea around the scientific basis of physical and cognitive exercise having a positive influence on slowing down the deteriation process of the brain.
Inspired by different products, like Dividat, that already exist on the market and yielding good results, we decided to create a product which is more fitting to the market. This is how we came up of combining a camera system with the latest cameravision models, to then giving the patients a way to interface with a game trainer, displayed on their television. To test our hypothesis we built a simple prototype and tested it with a handfull of people. By making the whole startup process fully automatic and gamificating repetitive tasks, we envision Neuranect to leave a positive impact on slowing down the dementia process.
Concept Overview
Competitor Analysis
User Research
Prototyping
Interface Design
Game Design
Industrial Design
Abstract: As part of a university module, we redid the user interface for ZVV ticket machines in Zurich from the ground up as a mock project. Our main aim was to enhance user experience and acessibility while working with the constraints of the current ticket machines, like a bad touchscreen and a screen with bad viewing angles. Through multiple design sprints, resulting in many iterations, and thorough user testing, we created a prototype of our design proposal.
Process & Context: With the task of re-envisioning the ZVV ticket machine user interface in mind, we first researched on transportation ticket machines worldwide to find out how every other public transportation provider does it. Through a heuristic evaluation and talking to a lot of users, we pointed the problems plaguing the user experience of current ZVV ticket machines.
To really get into the topic, we also contacted the team behind the current design, which gave us insights on their process. In design sprints, we iterated over many different new variants of possible design solutions, and tested each one of them using different methods, like heatmaps and A/B testing.
This gave us a lot of different insights on the users behaviour, helping us to refine our design further, ensuring accessibility and clarity in wording. Despite hurdles, especially concerning the zone-related complexities of the ZVV public transport network, our commitment paved the way for a user-friendly ticket purchasing process, resulting in a well rounded and accessible solution.
Competitor Analysis
User Testing & Persona Creation
Wireframing
Selected Final Screens
Abstract: Evoling from the concern over systemic issues, we addressed misleading layouts and tactics employed by grocery stores, promoting goods that may harm the environment and contribute to climate issues. Localista is a scaleable collection of UX and Service design guidelines (in form of a booklet), aimed at conventional stores to improve the customer experience of buying and increaseing the sales of regional and seasonal produce, creating benefits not only for custmers, but also regional farmers.
Research & Ideation
User Testing
Store Layouts
GitHub Repository / Interactive Visualization
Abstract: To visualize the carbon storage potential both below and above the Earth's surface, we teamed up with ETH Crowther Lab and Focus Terra to create an interactive table. This innovative tool enables exhibition visitors to delve into nature-based solutions for CO₂ storage and grasp intricate global climate data. Our goal is to educate and ignite inspiration, particularly among younger individuals, regarding the crucial issue of climate change.
Prototyping
Final Product
Abstract: Have you ever seen a drawing robot? Probably. But have you seen one that can draw upon your direct request on what to draw? TsunComp does exactly that. The pipeline we developed is a fully automated speech to machine code process, that uses GPT3.5 and StableDiffusion at its core. It sends out the data to a nicely designed plotter that then draws the generated image for you using a pen, which results in a physical memory that you can hold on to. Everything fully automated.
Prototyping
Final Product
Abstract: Sonora Lab focuses on the development of a body-music interface that enables individuals to create music and sounds through physical movement alone. Using machine learning algorithms and sound synthesis techniques, the system interprets gestures movements into musical elements, allowing users to express themselves creatively without relying on traditional musical instruments or technical expertise. We provide a framework for artistic exploration through an interactive archive that enables a new discourse in revisiting experiences. Rest assured, we’ll be recording your movements solely for the creation of visuals, with no storage intended. However, if you prefer not to participate, feel free to explore our archive and discover our past projects.
Software Architecture
Exhibition
Screencast
Abstract: DataBreach is an audio game in which you have to defend yourself against virtual viruses. You have to quickly recognise sounds coming from one of the eight surrounding speakers and react to them by turning a cube in the direction of the corresponding sound source to collect points. The aim of this game is to sharpen your hearing and reflexes.