Home3D GIS & Digital Twin Simulation
3D + DIGITAL TWINS

See the system.
Then simulate what changes.

GeoLayers combines Cesium-based 3D scenes with an operational simulation layer for assets, demand, capacity, dependencies, failures and resilience scenarios.

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Browser-based GISGeoAI + spatial analyticsSouth African context
3D + OPERATIONS

Turn GIS assets into an operational digital twin

GeoLayers combines 3D scene visualisation with an operations and simulation layer. Users can see assets spatially, then model demand, capacity, outages, dependencies and interventions over time.

3D

Scene Studio

Visualise project features in a Cesium-based 3D environment and use project attributes to communicate asset context.

▦

Asset model

Map capacity, demand, status, criticality, failure probability, recovery time and dependency fields from an existing project layer.

Δ

Scenario simulation

Apply demand growth, capacity changes, outages and delayed interventions across a defined simulation horizon.

R

Resilience testing

Use seeded Monte Carlo stress testing to understand service-level risk and identify critical assets.

SIMULATION WORKFLOW

From static asset map to scenario model

A digital twin becomes useful when it can represent how the system behaves under changing conditions.

Define the asset systemIdentify assets, capacities, loads, dependencies and operational status in a project layer.
Build a scenarioSpecify demand change, failure shocks, capacity interventions or forced outage conditions.
Run through timeSimulate demand growth, outage duration, recovery and intervention activation across multiple periods.
Compare outcomesReview service level, unmet demand, offline assets and resilience metrics across baseline and intervention scenarios.
RESILIENCE METRICS

See where the system is vulnerable

GeoLayers exposes the operational indicators needed to understand whether a scenario improves or weakens the network.

  • Capacity utilisation and total served/unmet demand.
  • Asset availability and criticality-weighted service level.
  • Dependency cascades when upstream assets become unavailable.
  • P05, median and P95 service outcomes from Monte Carlo runs.
  • Critical-asset risk ranking based on outage frequency and criticality.
  • Scenario layers that can be mapped in both 2D and the existing 3D scene environment.
USE CASES

Useful wherever spatial assets behave as a system

Digital twins can support planning conversations before capital or operational decisions are made.

⚡

Utilities & infrastructure

Explore capacity, service gaps, failure dependencies and upgrade scenarios.

🏙

Urban systems

Represent facilities, transport or service assets in spatial context and compare future demand scenarios.

♻

Operational networks

Model aggregation, processing or logistics assets where failure at one point affects downstream performance.

✓

Resilience planning

Identify critical assets and test whether proposed interventions materially improve service outcomes.

Build an operational twin from your GIS assets

Start with an asset layer that already contains the identifiers and operational fields needed for the scenario.

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