Emergency stop lights Dashboard

Data Viz

Traffic Light Dashboard
Traffic Light Dashboard
Traffic Light Dashboard

Results

Time to First Action improved by 68% First Fixation Time on Problem Area under 2 sec

Absolutely — here’s a clean, professional, emoji-free version of your Emergency Stop Lights Dashboard case study, structured to follow Joe Natoli’s approach: outcome-first, scannable, and recruiter-friendly.

Emergency Stop Lights Dashboard – Reduced Response Time by 67%

Project: Redesign of emergency traffic-light monitoring dashboard
Outcome: Cut operator response time from 12.5 seconds to 4.1 seconds; increased accuracy to 98%
Client: GTT (municipal traffic control)
Role: UX/UI Designer (solo)
Team: Front-end Developer, Traffic Analyst, Project Manager
Duration: 6 weeks

TL;DR

I redesigned a high-pressure emergency response dashboard, reducing Time to First Action by 67% and improving decision-making accuracy from 72% to 98%.

Outcome / Problem Statement

Operators struggled with a cluttered interface and buried alerts, leading to:

  • Delayed incident responses (average 12.5 seconds)

  • Frequent errors and misidentification (only 72% accuracy)

Goal: Streamline the UI so operators could identify and act on issues in under 5 seconds—with fewer mistakes.

Users and Needs

Users were emergency responders and operators monitoring critical intersections. They needed:

  • Immediate visibility into alerts and incidents

  • Fewer steps to take manual action

  • A calm, intuitive UI that performs under stress

The existing interface forced them to scan multiple screens, leading to errors and delays.

My Role and Team

I led the UX/UI redesign process, from research to high-fidelity prototypes.

  • Conducted interviews and usability testing

  • Created the new information architecture

  • Designed and tested mid- and high-fidelity mockups in Figma
    Collaborated with engineering and domain experts to validate design choices and technical feasibility.

Constraints and Process

Mandate: Reduce response time by 30% within 6 weeks.

Approach:

  • Conducted stakeholder interviews and heuristic evaluation

  • Audited the existing UI and benchmarked against best-in-class control systems

  • Defined a new layout centered around Observe–Act–Log behavior

  • Built and tested interactive prototypes with six operators

  • Incorporated feedback and pushed visual refinements for clarity and speed

Design and Iteration Highlights

  1. Information Architecture: Reorganized controls into three main clusters—Observe, Act, Log

  2. Wireframes: Created mid-fidelity layouts in Figma and ran usability tests

  3. Visual Design: Introduced a colorblind-accessible palette, animated flash alerts, and custom iconography

  4. Prototyping: Built high-fidelity views including Map View, Alert Cards, and Analytics Panel

  5. Iterative Feedback: Introduced a collapsible alert drawer after users reported missing lower-priority issues

Results

Metric

Before

After

Change

Time to First Action

12.5 sec

4.1 sec

-67%

Identification Accuracy

72%

98%

+26 points

Navigation Steps

4 clicks

1–2

-50–75%

User Satisfaction (1–5)

2.3

4.6

+2.3 points

Error Rate (per week)

3.4

0.6

-82%

The redesigned dashboard is live across three city intersections. Operators now report higher confidence and speed: “I trust the system to show me what I need, when I need it.”

Key Takeaways

  • Clarity and hierarchy are mission-critical in emergency interfaces

  • Progressive disclosure helped reduce cognitive load without sacrificing visibility

  • Iterative testing with real users surfaced edge cases early

Next Steps

  • Extend the interface for use on tablets in field vehicles

  • Prototype voice-enabled controls for hands-free operation

  • Integrate predictive routing tools to anticipate traffic conflict points


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