Overview

Socian Technologies tasked our team with exploring drone mapping for emergency response, focusing on how dispatchers could visualize drone activity, communicate with officers, and manage incidents in real time.
We researched dispatcher workflows, analyzed competing drone systems, and designed a mapping interface intended for integration into Socian’s future products.

 

Problem

Dispatchers operate in high-pressure environments with overloaded screens, inconsistent data sources, and limited tools for understanding drone behavior.
Key challenges included:
• Lack of consolidated drone information in current CAD systems
• Difficulty tracking drone visibility, location, and status during incidents
• Overly complex or unfamiliar mapping interfaces
• Poor integration between drone feeds, unit locations, and dispatcher communication

These gaps make drone-assisted response harder—not easier—for dispatchers.

 

My Role

I contributed to:
• Researching dispatcher workflows and pain points
• Conducting comparative analysis of drone UIs
• Sketching early concepts and mapping layouts
• Designing mid- and high-fidelity wireframes
• Leading user-testing sessions with a 911 dispatcher
• Iterating designs based on operator feedback

 

Key Insights

From research and field visits with dispatchers:

• Dispatchers need simplicity, not more data
• Address points matter more than vegetation or detailed satellite imagery
• Color-coded units significantly reduce cognitive load
• Drone visibility controls (e.g., stealth mode) prevent unnecessary escalation
• Layers should be hidden by default because they are rarely used
• Dispatchers want the ability to add nuance to AI-driven drone behavior

 

Solution

We designed a 911 dispatcher-focused mapping interface that balances automation with operator control.

Core Features
• Dynamic Map Views – Default, dark mode, and satellite modes for visibility and situational analysis
• Drone Status Panel – Speed, altitude, battery, activity zone, and live camera indicators
• Incident Flow Screens – From call intake to drone arrival to after-action review
• Unit & Drone Toggles – Police, fire, medical, and drone visibility controls
• Historical Incident Explorer – Time-based filtering and quick access to past reports
• AI-Assisted Reports – A refined alternative to “chat with drone” for updating situational context

All design decisions were validated with real dispatcher feedback and refined to reduce cognitive load.

 

Impact

Our prototype helped Socian understand how drones should integrate into emergency workflows by providing:
• A dispatcher-first mapping experience aligned with CAD patterns
• Clear drone autonomy indicators to prevent confusion or misuse
• Improved situational awareness through controlled map layers and real-time updates
• A foundation for future AI-assisted features and 3D mapping capabilities

Dispatchers described the interface as more intuitive and less overloaded than current systems.

 

Next Steps

• Add onboarding customization so operators can set layouts they prefer
• Expand AI features for nuanced information updates
• Conduct additional concept testing with dispatchers nationwide
• Integrate more data from CAD “notes” into the map view
• Implement an override function for drone movement and decisions

 

Documentation

• High-Fidelity Prototype
• Research Report & Findings
• Design System & Sketch Archive