AI-powered computer vision that transforms ADNOC car wash stations into intelligent, queue-aware service points — reducing customer wait times by 40% and boosting throughput by 25%.
of ADNOC car wash customers report frustration with unpredictable wait times during peak hours
of potential customers leave when they see a long queue — revenue lost to competitors or deferral
current digital tools to check queue status before arriving — it's entirely walk-in and hope for the best
No new hardware required. Our AI connects to your existing camera infrastructure at each ADNOC station. Yango Tech's computer vision models process each frame in real time.
The system identifies vehicles in each bay (occupied, finishing, free), counts queue length, reads license plates, and predicts wait times using historical patterns and live data.
Queue status, wait estimates, and bay availability are pushed via API to the ADNOC app, in-station displays, Google Maps, or any third-party integration.
Check wait times before driving. Join a virtual queue remotely. Get notified when your bay is ready. Choose the nearest station with the shortest wait.
Multi-camera live monitoring. Throughput analytics per bay and per station. Predictive demand forecasting. Staffing optimization alerts.
Virtual queuing means customers commit before arriving. Dynamic pricing during peak hours. Cross-sell fuel, convenience store, and premium wash packages while they wait.
ADNOC becomes the benchmark for digital service station experiences. The queue module strengthens the ADNOC app ecosystem and increases daily active usage.
Customers see real-time bay availability, estimated wait times, and can join a virtual queue — all without leaving their car.
Find the nearest station with shortest wait
Station List View
You'll be notified when a bay is ready for you
Station Detail + Live Feed
| Position | Plate | Joined At | Wait Time | Type | Status |
|---|---|---|---|---|---|
| #1 | A 12345 AUH | 14:18 | 14 min | Virtual Queue | Notified — Bay 1 Ready |
| #2 | B 98712 DXB | 14:22 | 10 min | On-site | Waiting |
| #3 | C 55408 AUH | 14:26 | 6 min | Virtual Queue | Waiting |
| #4 | D 77201 SHJ | 14:29 | 3 min | On-site | In Queue |
The queue monitoring module is API-first. It can be embedded into the ADNOC app, displayed on in-station kiosks, or integrated into any third-party super-app.
The queue monitoring engine exposes a simple REST API. Bay status, queue depth, wait estimates, historical analytics — all available in real time for any application to consume. Works with the ADNOC app, Google Maps, Apple Maps, WAM, or any third-party service.
We'll deploy the AI monitoring system at three selected ADNOC stations for a 90-day pilot. No new hardware — we connect to existing CCTV infrastructure and deliver results within 2 weeks.