Zone-based gate seating for Phoenix Sky Harbor International Airport, built around traveler agency.
Solo Designer
Fall 2025 to
Winter 2026
Figma
Claude Opus 4.6
Google Gemini
Nano Banana
Smart IoT Environment
Smartphone
Three seating zones, Quiet, Standard, and Social, let travelers choose the kind of space they want
Overhead depth sensors and seat pressure sensors read the gate at zone level, never per person
Signage, lighting, and an optional app show where seats are open, stepping in more as the gate gets busier
Remove the 6-step claiming sequence travelers perform today
Recover the roughly 40% of seats that sit empty but socially claimed
Read at a glance in person, with the app strictly optional
At a Sky Harbor gate, roughly 40% of seats end up empty but socially claimed while travelers stand along the walls instead. As one put it, “me and the rest of the world are uncomfortable sitting here together.” The cause is a ritual every traveler performs, a 6-step boundary-protection sequence: enter and scan the room, pick the safest-looking seat, claim the seats beside them with bags, put on headphones to signal they want to be left alone, then hold that boundary until boarding. The environment creates the problem, not the passengers.
SmartGate splits the gate into three zones, Quiet, Standard, and Social, so choosing a seat becomes choosing a space. Sensors read how full each zone is, and signage, lighting, and app alerts respond as the gate fills. The zones read clearly in person; the app adds detail only for travelers who want it.
A quick walkthrough of the gate in action: the three zones, the sensing that reads them, and the companion app that follows a traveler from choosing a space to boarding.
Contextual Inquiry, Empathy Mapping, Journey Mapping, Smart Environment Design, UI Design, Prototyping
Just me + Claude as an AI design partner
Fall 2025 research; ~6 weeks of design, Winter 2026
The concept builds on my own ethnographic study of Sky Harbor's Terminal 4 gates, a space that moves roughly 50 million passengers a year. Three findings set the direction.
About 40% of occupied seats held bags rather than people, and seats between strangers went constantly unused. Travelers judge whether a seat is available by the people around it, not by whether it is empty.
9 distinct traveler identities with opposing needs, from the Anti-Social to the People Person, confirmed that one uniform gate layout cannot serve every passenger.
The fuller a gate gets, the harder travelers work to avoid each other. The moment someone walks into a crowded gate and scans for a seat is where a connected system can help most.
All three findings pointed at the same place: the gate creates the boundary problem, so the gate, not the traveler, should absorb it.
Field Research — 3 observation sessions and 3 interviews inside Terminal 4, plus a review of comparable transit environments
Define — empathy maps for the passenger and the gate agent, a 7-stage journey map, and a design focus
Concept — the three-zone gate layout and the smart environment visualizations
Companion App — high-fidelity screens, delivered as a clickable Figma prototype
I mapped two people, not one. The passenger map surfaced the anxiety underneath the claiming ritual: it spikes the moment a crowded gate comes into view, runs on thoughts like “is that seat too close? Will they think I’m weird?”, and leans on devices for privacy, with about 80% of travelers using one as a social shield. The gate agent’s map found the other half of the problem: their seat metrics say available while the room looks full, crowding is estimated by eye, and they absorb frustration over conditions they cannot control. The system had to help both, which is why the traveler app and the gate operations feed were designed as one product.
The journey map followed a passenger through seven stages, from pre-gate to boarding, and tracked emotion alongside behavior: anticipation on the walk over, an anxiety spike on entering, guardedness through claiming and signaling, fatigue by the time boarding is called. Friction peaks in the middle stages, surveying the room and settling in to wait, exactly where the environment offers no help. That narrow window is where SmartGate concentrates its effort.
Everything the Define work found compresses into one sentence: travelers at Sky Harbor gates spend real effort negotiating who sits where, so the design focus is to move that work off the traveler and into the environment.
Each zone is tuned to a different cluster of traveler identities, and the environment does the explaining: seating geometry, lighting, and signage make what each zone is for obvious at a glance. While the gate is quiet, the zones explain themselves; as it fills, the signs update, the lighting shifts, and the app can alert a traveler when the zone they want has space. Zone renders generated with Nano Banana.
The environment itself went through three passes: I mapped the full system onto the gate first, stripped it back to a clean render, then revised the space after design feedback. Base renders generated with Nano Banana.
A step back from the renders, this is the logic that runs the gate: physical-default, digital-optional. Sensors read each zone's social occupancy, and the environment shifts with the crowd, staying passive while a zone is quiet, turning active as it fills, and converting the zones into boarding groups once boarding is called. The same feed powers three tiers: the physical room for everyone, the app for travelers who opt in, and an operator dashboard passengers never see.
SmartGate lives inside Sky Harbor's own brand, part of the airport rather than another app to download and learn.
Gate B22 at a glance: every zone shows a photo of the actual space, a live seat count, and a plain word like Spacious, so travelers can choose before they walk in.
One zone up close: the ambient features, live availability, and a seat map that deliberately shows estimates, never assigned seats.
Preferences persist: save Quiet once, and on every future trip through Sky Harbor the app flags when it has space.
Zero seats is information, not a dead end: the app says Full honestly and offers to watch for an opening.
Boarding closes the loop: group progress, a live passenger count, and the zones clearing out as the gate empties.
A live, clickable Figma prototype of the SmartGate companion app: choose a zone, save it as a preference, and follow the flow through to boarding.
Every pain in the research traced back to the space itself: fixed forward-facing rows, clustered outlets, zero wayfinding for social availability. Reframing the gate as the thing being designed, rather than the passengers being managed, unlocked the whole concept.
Gate agents watch seat metrics say available while the room looks full, and they absorb the frustration for conditions they cannot control. The gate operations feed exists because an environment that helps passengers while leaving agents guessing solves half the problem.
The zones are designed to speak for themselves; the app adds detail only for travelers who want it. In a space where many people never open an app, the room itself has to be the primary interface.
Claude supported design feedback, system flowcharting, and rationale refinement; Nano Banana generated the base environment renders. The research, the problem framing, and every design decision stayed mine.
The clickable prototype covers the companion app, but the core bet is spatial. I’d test zone legibility with a scaled physical mockup before touching another screen.
Each zone serves named archetypes from the research, and that mapping is a hypothesis. I’d recruit travelers across the 9 identities and watch which zone they actually choose.
Zone-level sensing avoids tracking individuals by design, but the environment never tells travelers that. A system reading a room full of people should say what it senses and what it never stores.