Case Study4 min read
Aviation & Computer Vision

Real-time video analytics
for demand-driven cleaning.

Real-time video analytics and demand-driven insights moved an Australian airport from fixed cleaning schedules to intelligent, needs-based operations across 60+ bathrooms.

Industry
Aviation
Capability
Video Analytics · ML
Infrastructure
Existing CCTV · IoT Beacons
Bathroom Cleaning · Computer Vision · Aviation
60+
Bathrooms in scope across domestic and international terminals
RT
Real-time foot-traffic, dwell-time, and usage pattern detection
ML
Bespoke machine-learning models running on existing CCTV infrastructure
PoC
Proof of concept delivered — validated for terminal-wide scale-out

Fixed-interval cleaning didn’t fit real passenger flows.

The airport operates 60+ bathrooms across domestic and international terminals, servicing millions of passengers annually. Fixed-interval cleaning schedules didn’t account for real-time variability driven by flight schedules, peak periods, or passenger flows — creating unnecessary labour cost, resource waste, and missed service opportunities.

Our approach

From CCTV feeds to operational decisions.

Video feeds from bathroom entrances were processed in real-time using bespoke machine-learning models — surfacing foot traffic, dwell times, and usage patterns through interactive dashboards and operational alerting.

The Technology

Existing CCTV, reused. Bespoke ML, built for purpose.

The solution layered real-time video analytics and bespoke ML models onto the airport’s existing CCTV estate — eliminating new hardware investment while unlocking real-time operational visibility. IoT beacons added cleaner tracking and adherence measurement.

Real-Time Video AnalyticsBespoke ML ModelsIoT Beacon TrackingExisting CCTVInteractive DashboardsAutomated Alerting
Outcomes

From reactive cleaning to demand-driven operations.

Passenger satisfaction

Cleaning aligned to actual demand — improving the experience during peaks.

Labour cost

Right-sized cleaning effort by need rather than fixed schedule.

Resource waste

Consumables and effort reduced by avoiding low-demand cleans.

60+

Scalable across terminals

PoC foundation validated for expansion across the full bathroom estate.

Work with BI3

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to demand-driven operations?

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