People-counting cameras, LiDAR density sensors, and gate-level counts feed the twin.
Move millions, safely.
A scenario for pilgrim management at Makkah-scale. Real-time crowd density, flow direction, and choke-point detection — visualised on a digital twin of the holy site, so command can act before pressure builds. Watch the scenario with the voiceover for the full walkthrough.
Specifications.
- Status
- Demo scenario
- Sensing
- Cameras · LiDAR density · Gate counts
- Site model
- 3D twin (haram + plaza, every zone)
- Density unit
- Persons per m²
- Routing path
- Zone → Sector → Command
- Mobile dispatch
- Nearest ground team
- Coordination
- Multi-agency · shared map
- Render engine
- Unreal Engine + LiDAR
- Use cases shown
- Density · Flow · Choke-point detection
What this scenario shows
- Scene 03.1The site, mappedA 3D twin of the haram and surrounding plaza, every zone identified.
- Scene 03.2The crowd, countedHeat-mapped crowd density updated in real time from camera and sensor feeds.
- Scene 03.3The flow, tracedFlow direction and choke-point detection — the twin highlights where pressure is rising.
- Scene 03.4The team, dispatchedAlerts routed to command + ground teams before a situation becomes a crush.
How TwinMs applies
Per-zone capacity thresholds, 730-day historical baselines per ritual phase, anomaly detection.
Alerts cascade from zone → sector → command, with mobile dispatch to the nearest ground team.
Integrates with command-and-control authorities — the twin is the shared map across agencies.
Business value
Pre-empt the crush — route teams before pressure builds, not after.
Phase by phase — capacity planned per ritual, validated season after season.
One shared map across hundreds of zones and many agencies at once.
A year of post-event analytics every season — informs the plan for the next.
Same engine that runs a single building, scaled to a holy city.
