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

Leadership & Contribution

I led the design strategy and execution for V-Eye, transforming a complex technical brief ("Federated Safety – A new paradigm") into a coherent product experience that won stakeholder buy-in. In a 1.5-day hackathon environment, I served as the bridge between our engineering team's technical capabilities and the judges' need to understand societal impact—fast.

Strategic Design Leadership:

• Translated the hackathon brief into a clear product vision and user experience strategy

• Defined what we would build, in what order, and how to demonstrate value within tight constraints

• Facilitated rapid alignment sessions with data scientists and engineers to scope feasible solutions

• Structured the final pitch narrative to address technical credibility, business viability, and social impact simultaneously

• Made real-time prioritization decisions on what to prototype vs. what to illustrate

Cross-Functional Coordination:

• Worked embedded with data scientists to understand federated learning architecture and translate it into user flows

• Collaborated with DevOps engineer to ensure the technical stack could support the UI vision

• Partnered with innovation strategist to align our solution with MobilityXlab's strategic priorities

• Guided software engineering students on implementation details and interaction timing

• Synthesized input from multiple stakeholders (Volvo Group, Ericsson, RISE, city planners) into a unified design direction

Design & Prototyping Execution:

• Designed two complete dashboard interfaces (driver-facing + operator-facing)

• Built an animated 10-scene product narrative in Lovable to demonstrate end-to-end value

• Created a visual design system: icons, warnings, map overlays, state transitions, motion principles

• Ensured technical accuracy while maintaining clarity for non-technical judges

• Delivered a presentation-ready prototype that made complex federated computing tangible

This project required me to operate as strategist, designer, and project coordinator simultaneously—seeing the whole picture from technical architecture to user needs to pitch effectiveness.

Core Competencies Demonstrated:
Product Strategy · Design Leadership · Rapid Prototyping · Dashboard Design · Data Visualization · System Mapping · Interaction Design · Stakeholder Communication · Technical Translation · Presentation Design

Challenge

The Context:
CoTwin is a Vinnova/FFI-financed project led by MobilityXlab, bringing together CanaryBit, Volvo Group, Ericsson, RISE Research Institutes of Sweden (AstaZero), Lindholmen Science Park, and Göteborgs Stad to solve secure data-sharing challenges in transport.

The Problem:
Despite advanced sensors, vehicles still miss cyclists or pedestrians hidden behind buses, vans, corners, and structures. Cities collect massive mobility data, but fragmentation and strict privacy regulations (GDPR) prevent real-time sharing. Current systems operate in silos—vehicles can't "see" beyond their own sensors, and cities can't act on aggregated safety insights.

The Design Challenge:
Design a federated safety solution where vehicles, OEMs, and cities collaborate on collision prevention without exposing raw sensor data—and make it understandable to engineers, policymakers, and business stakeholders within a 1.5-day hackathon.

The Strategic Challenge:
Communicate highly technical concepts (federated learning, confidential computing, edge processing) through design in a way that feels real, actionable, and commercially viable.

How might we use CoTwin infrastructure to solve the lack of situational awareness for drivers and limited visibility for cities—and present it clearly to both technical and non-technical audiences?

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

Approach

I took a user-centered narrative approach to a deeply technical problem—starting with the human impact, then reverse-engineering the system architecture into understandable flows.

Phase 1: Strategic Framing (Hour 1-3)

I facilitated a rapid discovery session with the team to answer:

• Who are our users? Drivers, fleet operators, city planners, OEMs

• What's the core value? Collision prevention through shared perception

• What's the technical constraint? Privacy-preserving, decentralized data processing

• What's the business model? Licensing to cities, OEMs, fleet operators

• What do judges need to understand? Problem → Solution → Impact in under 5 minutes

From this, I defined two primary design outputs and one strategic narrative tool:

Phase 2: System Mapping & UX Structure (Hour 4-8)

I broke down the Federated Safety concept into user-facing flows:

• Where does data originate? (OEM sensors, city CCTV, Trafikverket collision data)

• How do disparate sources merge? (Confidential VM, edge computing)

• How is privacy preserved? (Anonymization pipeline, encrypted data flow)

• How do predictions reach drivers? (Real-time alerts, risk scoring)

• How does the city benefit? (Aggregated insights via digital twin, no raw data exposure)

This system map became the foundation for both dashboard designs and the animated story.

Phase 3: Design Execution (Hour 9-24)

I designed and built three interconnected experiences:

1. Driver Dashboard (Tesla Model Interface)

Created a clean, driver-focused UI showing:

• Real-time risk detection (blind spot alerts, proximity warnings)

• Trip history and safety scoring

• Nearby incidents and hazard warnings

• Visual representation of what the vehicle "sees" beyond its own sensors

Design decisions:

• Dark theme for nighttime driving clarity

• Neon accent colors (safety-critical actions)

• Minimal cognitive load (glanceable, no dense text)

• Progressive disclosure (details available, not intrusive)

2. Operator Dashboard (Fleet/City Management)

Built a high-level command center for:

• Multi-camera fusion monitoring (OEM + city infrastructure)

• Data pipeline visualization (ingestion → processing → prediction)

• Live map with collision hotspots and near-miss tracking

• Anonymization verification and compliance monitoring

Design decisions:

• Information density balanced with scannability

• Color-coded alert system (green/yellow/red)

• Clear data lineage (what's coming from where)

• Trust indicators (encryption status, anonymization confirmed)

3. Animated Product Narrative (Lovable)

To ensure judges understood the complete story, I structured a 10-scene animated presentation:

1. The visibility problem (vehicles can't see around obstacles)

2. Cost of collisions (societal + economic impact)

3. Decentralized multi-camera network (how it works)

4. Anonymous data pipeline (GDPR compliance + confidential computing)

5. Real-time prediction engine (federated learning explained visually)

6. Collision avoided sequence (driver receives alert, reacts in time)

7. City-scale value (aggregated insights without privacy violation)

8. Business model (licensing to OEMs, cities, fleet operators)

9. Technical architecture (edge + cloud + confidential VM)

10. Impact projection (scalability and societal benefit)

Narrative design principles:

• One concept per scene (reduce cognitive load)

• Slow, deliberate transitions (allow comprehension)

• Strong visual metaphors (encrypted data = blurred faces + lock icons)

• Consistent design language (dark theme, neon accents, soft motion)

Phase 4: Team Coordination & Iteration (Hour 25-36)

• Conducted rapid review cycles with data scientist to ensure technical accuracy

• Aligned with innovation strategist on business positioning

• Tested prototype flow with team to identify confusing transitions

• Refined warning states and alert timing based on engineer feedback

• Prepared pitch delivery structure (who presents what, when to demo)

Activities.
Strategic Framing · Cross-Functional Facilitation · System Flow Mapping · Dashboard UI Design · Data Visualization · Warning State Design · Confidential Computing Flow Visualization · Motion Design & Storyboarding · Interaction Design · Figma to Lovable Implementation · Rapid Iteration · Pitch Structure

Result

Product Delivered:
A convincing, presentation-ready federated safety concept that demonstrated real-world viability:

Clear societal impact: Showed how vehicles can "see" beyond blind spots, preventing collisions
Technical credibility: Demonstrated understanding of federated learning, confidential computing, and edge processing
GDPR compliance: Visualized privacy-preserving data pipelines that cities and OEMs could trust
Commercial viability: Outlined licensing model attractive to multiple stakeholders (cities, OEMs, fleet operators)

Design Outputs:

• Working driver dashboard UI (Tesla-style interface)

• Operator dashboard for fleet/city management

• Animated 10-scene product narrative (Lovable)

• Complete visual design system (icons, warnings, map overlays, state transitions)

• Data fusion flow diagrams explaining technical architecture

Strategic Outcome:
The final pitch was fast, visual, and technically credible—enabling non-technical judges to understand complex federated computing while giving technical judges confidence in our approach. Our design work made an abstract concept feel real and actionable.

Team Impact:
By establishing clear design direction early, I enabled engineers to focus on technical feasibility while I handled user experience and presentation strategy. This division of labor maximized our 1.5-day timeline.

Learnings

On translating complexity:
This project reinforced that clarity is a design skill—not just an outcome of simplicity, but a result of strategic information architecture.

On cross-functional leadership under pressure:
In hackathon conditions, design leadership means making fast, confident decisions while staying open to technical constraints. I learned to facilitate alignment quickly, communicate design rationale concisely, and adapt in real time without losing sight of the end goal.

On seeing the whole picture:
This project demanded simultaneous thinking across multiple layers: user needs (drivers, operators, cities), technical architecture (federated learning, edge computing), business model (licensing, partnerships), and presentation strategy (what will convince judges).

On data accessibility:
Working with Trafikverket's collision data opened my eyes to how much mobility information is publicly available but underutilized. This inspired thinking about how better design and data infrastructure could unlock societal value from existing datasets.

Takeaway.
I transformed a complex federated safety concept into a readable, engaging product story—backed by functional UI prototypes that made the idea feel tangible and actionable within 1.5 days.

The project demonstrated that design is a strategic tool for making emerging technologies (edge computing, confidential computing, multi-camera fusion) understandable and commercially viable.

Future potential: This concept could scale to smart city infrastructure, autonomous vehicle fleets, and insurance risk models—all areas where privacy-preserving data sharing unlocks value.

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