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iQueue Changi

Leveraging AI and IoT to optimize passenger flow at Changi Airport

iQueue Changi

Leveraging AI and IoT to optimize passenger flow at Changi Airport
my role

UI/ux Designer

Industry
Aviation
Timeline
feb 2024
(2 weeks Sprint)
Overview

Optimizing Airport Flow with AI & IoT

Navigating Changi Airport can be overwhelming, with unpredictable queue times at check-in, immigration, and boarding gates. Travelers often find themselves rushing last minute, unsure of wait times, and struggling with unclear wayfinding.

Recognizing this challenge, I led the design and research for iQueue Changi, an AI and IoT-powered queue management system aimed at optimizing passenger flow. By integrating real-time data, predictive analytics, and smart navigation, iQueue Changi helps travelers plan their journey with confidence, reduce waiting times, and move through the airport seamlessly.
The result? A stress-free, data-driven experience that improves both passenger satisfaction and airport efficiency—ensuring smoother journeys for millions.
Not interested in the design process?
JUMP TO FINAL DESIGN
Highlights

An AI-Powered Solution for Smarter Queues

iQueue Changi leverages AI and IoT to provide real-time queue tracking, predictive wait times, and smart wayfinding, helping travelers navigate Changi Airport seamlessly. By optimizing passenger flow, the system reduces congestion, improves efficiency, and enhances the overall airport experience.

Context

Changi Airport – Balancing Growth with Efficiency

As the 4th busiest international airport in 2024, Changi Airport handled 67.7 million passengers, maintaining its reputation for efficiency and world-class service. However, with increasing traveler volume, managing passenger flow remains a growing challenge.

While innovations like automated clearance and biometric processing have improved efficiency, real-time queue visibility is still limited, leaving travelers uncertain about wait times. Recent incidents, such as the passport-less clearance system issue at Terminal 1, highlight the need for more robust congestion management solutions.

To sustain its Skytrax top rankings and ensure smooth operations, Changi must enhance predictive queue tracking and passenger movement optimization in the years ahead.

PROBLEM

Navigating Changi Airport ISN’T as seamless as it should have been.

Unpredictable Queue Times

Travellers often encountered long and inconsistent wait times at check-in, immigration, and boarding, making it difficult to plan ahead.

Limited Real-Time Information
Existing solutions, like static signage and mobile apps, provided outdated or generic estimates, leaving travelers without accurate, up-to-the-minute insights.
Inefficient Passenger Flow
Without a data-driven approach to queue management, congestion remained poorly optimized, impacting both traveler experience and airport operations
Research

Understanding Passenger Pain Points

To design an effective solution, we needed to understand how travelers experience queues at Changi Airport. During the research phase, I conducted a detailed survey to gather quantitative data on passenger behaviors, frustrations, and expectations regarding queue times, navigation, and real-time information.
The survey provided key insights into how travelers interact with queue management systems and highlighted the gaps in existing airport navigation solutions.
INSERT DISCLAIMER TEXT & SURVEY INFO (NO. OF PARTICIPANTS OVER X DAYS.) ALL DATA COLLECTED IS ANNOYMOUS.

Nearly 96% of travelers have experienced confusion or difficulty navigating the airport at least once, highlighting the need for better wayfinding and real-time information.

Over 33% of respondents reported missing or nearly missing a flight due to unexpected queue delays, indicating a critical gap in queue visibility and time management.

More than 83% of travelers said they would consider using AI-powered queue tracking, demonstrating strong demand for a smarter, predictive solution.

Research

Deep Dive into AI & IoT in Queue Management

To build a data-driven, real-time queue management system, it was crucial to understand how AI and IoT technologies could be applied effectively. This involved researching existing solutions, their limitations, and how advanced predictive analytics and IoT-powered tracking could enhance Changi Airport’s efficiency.

Through this deep dive, I explored how AI models predict queue congestion, how IoT sensors track passenger flow, and what technology stack would support seamless integration into airport operations.
AI-Powered Queue Prediction

Traditional queue management relies on fixed estimates and historical trends, which often fail to reflect real-time conditions. AI-driven queue prediction uses machine learning models that analyze:

  • Live passenger movement data from IoT sensors
  • Historical queue trends to predict future congestion
  • External factors like flight schedules, time of day, and staffing levels

By implementing real-time AI-based predictions, airports can proactively manage congestion rather than reacting after queues build up.

IoT Sensors & Real-Time Flow Tracking
IoT-enabled smart sensors provide accurate, real-time movement tracking without the need for manual input. Key technologies include:
  • LiDAR sensors – Monitor crowd density and movement patterns
  • Ultra-Wideband (UWB) Beacons – Enable precise indoor positioning for passengers
  • Thermal Cameras – Detect queue buildup at immigration & boarding gates
  • Edge Computing – Processes data on-site for instant analytics, reducing delays in queue updates
With these technologies, airports gain a live overview of passenger distribution, allowing for better resource allocation and smoother flow.
AI + IoT = A Smarter Airport Experience
By integrating AI predictions with IoT-based tracking, queue estimates become more accurate, passengers receive real-time updates, and airport staff can optimize operations dynamically. The combination of these technologies creates a system that is:


✅ Proactive, not reactive – Predicts queues before they form


✅ Personalized – Adjusts recommendations based on traveler data


✅ Seamless – Works in the background without disrupting passenger flow

Research

Existing Technology & VendorS

To build a robust and scalable queue management system, I analyzed existing AI and IoT technologies used in airports worldwide. This research provided insight into proven solutions, vendor capabilities, and best practices for integrating real-time queue tracking at Changi Airport.

Amazon Web Services

AI-powered queue prediction, cloud computing, edge processing.
Los Angeles International, London Heathrow

Veovo

AI queue management, real-time congestion analytics

John F. Kennedy International, Amsterdam Schiphol

Wavetec

Digital queuing & crowd flow optimization

Toronto Pearson, King Abdulaziz International
Research

How Do Other Airports Handle Queue Management?

To understand how global airports manage passenger flow, I conducted a competitive analysis of leading airports that have implemented AI and IoT-powered queue management systems. This helped identify existing solutions, gaps, and opportunities for Changi Airport to improve its queue efficiency.

Airport

AI Queue Prediction

IoT Indoor Navigation

Chatbot Assistance

Real-Time Queue Tracking

Changi Airport (Before iQueue)

❌ No

❌ No

❌ No

❌ No

Heathrow Airport

❌ No

✅ Yes
(AR Navigation)

✅ Yes

❌ No

JFK Airport (New York)

✅ Yes
(AI-Based)

No

❌ No

✅ Yes

Hong Kong International

✅ Yes
(IoT-Based)

✅ Yes

❌ No

✅ Yes

Key Takeaways:
  • Changi lacks AI-driven queue prediction and IoT-based real-time tracking, creating an opportunity to improve passenger experience with live queue updates.
  • Hong Kong International Airport & JFK have implemented AI queue prediction models, reducing wait times and improving passenger flow.
  • Heathrow focuses more on AR-powered wayfinding, which improves navigation but lacks predictive queue management.
Opportunities for Changi Airport:
  • Combine AI queue prediction (like JFK) with IoT-powered navigation (like Hong Kong Int’l) to create a best-in-class queue management system.
  • Integrate real-time passenger alerts & smart wayfinding to provide a seamless end-to-end experience.
  • Leverage AWS cloud computing for AI & edge processing, enabling low-latency queue updates.
Key Strengths & Weaknesses of Existing Solutions:

•  Heathrow Airport
Strong on Navigation, Weak on Queue Prediction

✅ Augmented Reality (AR)-powered wayfinding helps passengers navigate efficiently.


❌ No AI queue prediction, meaning congestion still occurs unexpectedly.

• JFK Airport
AI Queue Prediction, but Lacks IoT-Powered
Indoor Navigation

✅ AI-driven queue analytics improve processing times at TSA security checkpoints.


❌ No integrated indoor navigation, leaving passengers reliant on static signs.

• Hong Kong International Airport
Balanced AI & IoT Integration

✅ IoT-based queue tracking + AI predictions make it one of the most efficient systems.


❌ Limited chatbot assistance, meaning passengers still rely on airport staff for inquiries.

Research

User Journey

Meet Emily, a frequent traveler who loves the efficiency of Changi Airport but often struggles with unpredictable queue times. Without real-time insights, she relies on guesswork to plan her journey, leading to unnecessary stress, rushed decisions, and missed opportunities to relax or shop. This section explores her experience, highlighting how the lack of queue visibility, inconsistent wayfinding, and last-minute congestion impact her airport journey.

Emily Tan – The Leisure Traveller

Age: 27 | Solo Traveler | Travels 2-3x a year

Arrival at Airport

Arrives 3 hours before flight

Check-In

Uses kiosk to check in and drop off baggage

Immigration
Heads to ICA Automated Clearance gates
Terminal Exploration
Wants to grab
coffee and relax
Boarding
Wants to grab
coffee and relax

😊


Excited for a short holiday to a nearby destination but unsure about the check-in.

🫤


Doesn’t know how much time she has before moving to immigration.

🤩


Changi’s automated clearance is efficient

😨


Afraid of missing boarding time, keeps checking flight screens manually

🫨


Rushes last minute after hearing a boarding announcement

IDEATION

Developing a Solution

iQueue Changi is designed to enhance the airport experience by providing real-time queue predictions and smart navigation powered by AI and IoT. The system enables travelers to make informed decisions about their journey, ensuring smoother transitions between check-in, security, immigration, and boarding. By integrating live wait-time data, personalized alerts, and dynamic wayfinding, iQueue Changi eliminates the uncertainty of airport queues and empowers travelers with actionable insights.

AI-Powered Queue Prediction & Checkpoint Tracking

Stay informed with live queue updates at check-in, immigration, and security, allowing travelers to plan their journey with confidence before reaching the airport.

  • Provides real-time queue tracking for check-in, immigration, and security.
  • Travelers can view estimated wait times before choosing a checkpoint.
  • Live data updates help passengers plan their journey better.

Real-Time Gate Timing & Boarding Readiness

Stay informed with live queue updates at check-in, immigration, and security, allowing travelers to plan their journey with confidence before reaching the airport.

  • Provides live gate assignment updates and boarding time countdowns.
  • Notifies travelers when boarding is about to begin, reducing rushes.
  • Suggests the optimal time to leave for the gate, factoring in walking distance and congestion.
Final Design

A Smarter, Stress-Free Airport Experience

The final design of iQueue Changi prioritizes efficiency, clarity, and user control, ensuring a seamless airport journey. I focused on integrating real-time queue predictions, intuitive wayfinding, and automated notifications to eliminate travel uncertainty. With smart AI-driven queue monitoring, travelers no longer have to guess wait times. Dynamic wayfinding and congestion-based route suggestions guide users efficiently through check-in, immigration, and boarding, reducing stress and improving punctuality. Real-time baggage tracking ensures a hassle-free arrival experience, giving passengers full visibility of their luggage status. Each feature was designed to provide clear, actionable insights, allowing travelers to navigate Changi Airport with confidence and ease.

Not Sure About Wait Times? Get Real-Time Updates

Gone are the days of blindly heading to a checkpoint, unsure of the queue length. iQueue Changi provides live queue predictions for check-in, immigration, and boarding gates, ensuring travelers make informed decisions. With real-time updates, users receive alerts if wait times increase, allowing them to adjust their schedule accordingly.

How it works:
  • Travelers see real-time queue estimates before heading to a checkpoint.
  • Automated notifications alert users if congestion increases.
  • Live data refreshes ensure travelers always have the latest information.

Worried About Last-Minute Gate Changes? Stay Notified Instantly

Flight gates sometimes change unexpectedly—iQueue Changi ensures passengers receive immediate alerts
so they can quickly adjust.

How it works:
  • Gate change notifications alert users instantly if their gate is reassigned.
  • Alternative walking routes are provided in case of last-minute changes.
  • Ensures passengers reach their new gate efficiently without confusion.
Post design

My Key Takeaways

User needs drive meaningful solutions – Research reinforced that real-time queue visibility and smart notifications were key to reducing traveler stress.

AI & IoT are transforming airport experiences – Leveraging real-time data, predictive analytics, and IoT sensors allows for more efficient passenger flow and smarter decision-making.

Industry benchmarks provide valuable insights – Studying other airports helped shape a more competitive and effective solution for Changi.

Real-world constraints shape digital experiences – Designing for physical movement, congestion,
and airport layouts was just as important as UI/UX decisions.