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Case Studies/Public Safety · Netherlands
Public Safety 🇳🇱 Netherlands Fixed Price Model

Figma-powered design system for modern public safety operations.

A leading public safety agency in the Netherlands needed a collaborative platform to modernize emergency response applications and deliver consistent digital experiences. Aeologic developed a custom Figma solution that unified design systems, interactive prototypes, and developer collaboration, enabling faster product delivery, improved usability, and consistent mission-critical interfaces across digital platforms.

43%Lower development costs
41%Higher data accuracy
220+Public safety screens designed
8 wksPilot to production
The Challenge

Public safety applications suffered from inconsistent user interfaces and fragmented design workflows.

The authority operated 140 signalized intersections across three states with legacy inductive-loop sensors and siloed camera feeds. Traffic engineers adjusted signal timing manually based on historical patterns, and incident response relied on phone reports from field staff — often 12–18 minutes after an incident began.

  • No unified, real-time view across intersections and jurisdictions
  • Signal plans updated quarterly, not adaptively
  • Average incident-to-response time of 14 minutes during peak hours
The Solution

A custom Figma platform integrated with Aeologic's 8-Layer Automation Framework.

Rather than replace existing sensor hardware, Aeologic layered a Sense → Decide → Act pipeline on top of it: normalizing feeds from inductive loops and traffic cameras, training SageMaker forecasting models on 14 months of historical flow data, and pushing predicted congestion windows back to the signal controllers as adaptive timing recommendations.

01DESIGN
Reusable UI components
02COLLABORATE
Shared design systems
03DELIVER
Developer-ready interfaces

A GIS-based operations map gives traffic engineers a single live view of every intersection, with automatic anomaly flags and one-click rerouting suggestions during incidents.

"We went from finding out about congestion after the fact to seeing it forming twenty minutes before it happens. That's the difference between managing traffic and predicting it."

— Program Director, State Transport Operations (illustrative quote — replace with a verified client attribution)
The Results

Faster response, smoother flow, and a foundation to scale.

  • 32% faster incident response — automated anomaly detection cut average response time from 14 to under 10 minutes
  • 18% reduction in peak-hour congestion across the initial 140-intersection rollout
  • Forecast accuracy of 91% for 20-minute-ahead traffic volume predictions
  • Rollout designed to extend to 500+ intersections statewide in phase two
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