The IoT in aviation sector was estimated at $1.59 billion in 2024, with a CAGR projection of 21.7% through 2034.
In today’s busy air traffic environment, you can’t just keep adding terminals. Airports need to evolve into ecosystems of awareness, adaptation, and prediction. At the heart of this evolution is a triad of IoT, AI, and Cloud systems. Together, they can drive a next-gen ops for airports.
The Landscape & Growth Trajectory
The aviation cloud market has previously been reported at a value of USD 6.19 billion in 2023, with expectations of annual growth being 12.5% a year. Market research indicates that there are more than 4,500 airports around the world that have already adopted some form of cloud platform for passenger processing or baggage handling, covering nearly 70% of the commercial airports globally.
These are not small remote projects, they are macro industry shifts.
How the Stack Works in Practice
IoT as the Sensing Layer
Airports install sensors throughout terminals, on baggage claim belts, gates, HVAC systems, walkways and infrastructure. The data streams give them real-time awareness across touchpoints like queues, equipment status and crowd density.
The Role of AI as The Intelligence Layer
IoT can be leveraged with data fed into AI models for prediction, anomaly detection, and recommendation. For example:
- Predicting passenger traffic peaks and staffing requirements
- Forecasting equipment failures
- Real-time optimization of gate assignments
- Simulating ‘disruption scenarios’ (e.g. delay, weather) using digital twins
The Platform Layer: Cloud (and Edge)
The cloud solution supports aggregation, scalability, integration, and computing-intensive tasks, such as model training and analytics at scale, while edge computing supports ultra-low-latency applications, such as video analytics and alerts, at the point of data capture. Airports like Bangalore and Singapore already employ a hybrid architecture, the cloud for scale, and edge for responsiveness.
Use Cases That Matter
Digital Twins as a Turnaround Management System: Aberdeen airport employed a digital twin model to synchronise visibility across dashboards used by ground handling operations, gate operations, and scheduling to enhance the visibility of turnaround.
Predictive Maintenance: Sensors track vibration, temperature, and usage patterns for conveyor belts at boarding gates and other moving elements such as escalators or HVAC systems. This enables AI to flag rising anomalies before failures that could cause downtime occur.
Crowd Analytics and Queue Length Prediction: AI models recognise and track growing queues via video and sensor fusion. This allows staff and stakeholders to streamline resource allocation like change shifts or open extra lanes.
Energy Optimisation: IoT allows monitoring of occupancy, as well as ambient conditions such that the AI can adjust lighting, cooling, heating in real-time, allowing for significant overall annual reduction in electrical consumption over time.
IoT provides airports with its eyes and ears. AI provides the brain. Cloud provides scale and coherence. Each of those by itself can have substantial impact, but when aligned in systematic tandem, they can fundamentally change what an airport can be. For airports preparing for the next ten years of passenger growth, that stack is foundational.
At WAISL we empower airports with next-gen technologies to enable digital transformation. Contact us to know more.
