Client: MobilityXlab Gothenburg
Industry: Automotive · Mobility Technology (Smart Mobility / Vehicle Safety Systems).
Timeline: 1.5 days | November 2025
My Role: UX/UI Designer, Interaction Prototype Lead
Team: Data Scientist, DevOps Engineer, Senior Innovation Strategist, 2× Software Engineering students

Contribution

I led the UX/UI direction of our concept V-Eye, a real-time, privacy-preserving safety network for vehicles and cities. My responsibility was to turn the hackathon brief (“Federated Safety – A new paradigm”) into a clear product experience, creating:

• A responsive vehicle dashboard UI (Tesla-style interface for drivers)

• An internal multi-camera fusion dashboard for operators (our company side)

• A complete animated product narrative built in Lovable, covering risk detection, data flow, confidential computing, and the digital twin

• Visual system design: icons, warnings, map overlays, interaction timing, and state transitions

I shaped the end-to-end story so the judges could understand the technical, societal, and business impact within minutes.

Competences.
Federated Safety UX · Edge-computing UI flows · Animated storytelling · Dashboard design · Data visualization · System mapping · Interaction design · Rapid prototyping (Lovable) · Multi-stakeholder communication

Challenge

CoTwin is a project led by MobilityXlab and financed by Vinnova / FFI that brings together CanaryBit, Volvo Group, Ericsson, RISE Research Institutes of Sweden (AstaZero), Lindholmen Science Park, and Göteborgs Stad to solve the transport industry's challenges with secure data sharing.

Despite advanced sensors, vehicles still miss cyclists or pedestrians hidden behind buses, vans, corners, and building structures. Cities also collect massive mobility data, but fragmentation and strict privacy rules mean nobody shares it in real time. The hackathon challenged us to design a solution where vehicles, OEMs, and cities collaborate on safety without exposing raw sensor data.

How might we use CoTwin to solve the lack of upcoming situational awareness for drives and limited visibility for cities — and present it clearly to both engineers and policymakers?

Approach

We started by breaking down the technical requirements from the Federated Safety concept into understandable user flows: where data originates, how sensors from different sources (OEM, CCTV, city cameras) merge, how anonymisation happens in a confidential VM, how predictions and alerts reach drivers, how a city digital twin receives aggregated insights. We had to work with Decentralized Systems and Confidential Computing concepts and create a high social impact.

From that, I built two core experiences:

1. Driver Dashboard (Tesla Model Example)

A clean visual interface showing:

• Real-time risk detection

• Blind spot alerts

• Trip history

• Safety score

• Nearby incidents & warnings

• A simple mental model of what the car “sees” beyond its own sensors

2. Operator Dashboard (Company Side)

A high-level view of:

• OEM cameras

• City infrastructure

• Trafikverket collision data

• Data fusion pipeline

• Prediction engine

• Live map with hotspots, near misses, and alerts

3. Animated Story (Lovable)

To pitch effectively, I structured the narrative into clear, slow transitions:

• The visibility problem

• Cost of collisions

• Decentralized multi-camera safety network

• Fully anonymous data pipeline

• Real-time prediction

• Collision avoided sequence

• City-scale value model and licensing

I designed everything to stay consistent: dark theme, neon accent colors, soft motion, clear icons, blurred faces, encrypted-data visuals.

Activities.
UX Structure · System Flow Mapping · Dashboard UI · Warning States · Confidential Computing Flow Visualization · Motion & Storyboarding · Interaction Design · Figma to Lovable Implementation · Rapid iteration with engineers

Result

We delivered a convincing real-time safety concept that showcased the societal impact of federated perception:

• A clear demonstration of how vehicles can “see” beyond their own blind spots

• A working UI prototype for both driver and operator views

• An explanation of decentralized computing + confidential analytics

• A compelling animated narrative that connected all moving parts

Our solution showed how shared perception reduces accidents while staying GDPR-safe, making it attractive for cities, OEMs, and fleet operators. The final pitch was fast, visual, and technically credible thanks to the coordinated UI + animation work.

Deliverables.
Animated 10-scene Lovable presentation 16:9 · Driver dashboard UI · Internal operator dashboard · Data fusion flow diagram · UI components, icons, and color/alert system · Story structure for the pitch

Learnings

Compressing a technical product into a clear, intuitive narrative is a design challenge in itself. The key is reducing cognitive load: one idea per frame, slow transitions, strong visual metaphors, and consistent iconography. Collaborating with data scientists and engineers in real time helped align the storytelling with the underlying architecture.

Takeaway.
I turned a complex federated safety concept into a readable, engaging product story, backed by UI prototypes that made the idea feel real. The project reinforced how design can clarify emerging technologies like edge computing, confidential computing, and multi-camera fusion — making them understandable and actionable. I also got an idea of how much data traffikverket.se has, and an understanding of how much information is actually available to the public.

Lovable Prototype: https://preview--streetview-aware.lovable.app/