A live digital copy of your city, on a single screen.

Terrain, roads, parcels and green spaces sit on a 3D base in the same coordinate system as your city information system, covering the whole region from the mountains to the sea.

• City information system and GIS data in one model
• Real terrain from the elevation model
• The entire region, including rivers, coast and mountains

Every building rises with its floor heights, façade and roof. Critical structures are built in detail, the rest of the city at a performance-friendly level of detail.

• LOD2 citywide, LOD3 for critical structures
• Hospitals, stations, bridges and viaducts
• The same model in the browser, on desktop and in VR

When vehicle tracking and counting data are connected, traffic, buses and rail vehicles move through the model at their real positions, and every road segment shows its current density in colour.

• Vehicles at their real positions
• Density per road segment
• Flow speed and congested segments

Every device in the field connects to the digital twin, whatever its brand. Air quality, noise, meter and structural sensors live at their exact positions in the model; when a threshold is exceeded, the responsible department is notified instantly.

• Hardware-agnostic device management
• Edge pre-processing, encrypted transmission
• Smart threshold-based alarms

Phase, queue and waiting-time data for every intersection is reflected in the twin. Signal timings are tested in the model before they are applied on the street; city cameras are placed at their real positions on the map, and incidents open with a single click.

• Real-time congestion and bottleneck detection
• Adaptive signal scenarios
• Geolocated cameras and incident detection

Lines and stops take their place on the city’s 3D map. Once your vehicle tracking system is connected, every bus appears at its position on the line; estimated arrival at the stop and vehicle occupancy are monitored on the same screen.

• Line and stop network on one map
• Vehicle position and occupancy
• Estimated arrival time at the stop

The tram line sits in the model with its stops and intersection crossings; services are animated from line and stop data. Headways and waiting times at stops are monitored live once your organisation’s systems are connected.

• Animated from line and stop data
• Headway and waiting time
• Assessed together with intersections

Metro tunnels and stations appear below ground together with underground infrastructure such as water and energy lines. Station entrances meet the streets and stops above ground in the same model.

• Tunnels and stations in 3D
• Together with underground infrastructure
• Linked to transfers above ground

Hospitals are added to the model together with their energy, water and generator infrastructure. Emergency department load and ambulance access times are tracked on the map; in a disaster, healthcare capacity is planned alongside the distribution of casualties.

• Critical infrastructure and backup power
• Ambulance access analysis
• Capacity planning in disasters

The building stock is shaken with earthquake scenarios of different magnitudes; buildings that may be damaged and roads that may be blocked are visible in advance. Assembly and shelter areas stand out on the map, and evacuation routes to them are drawn along the roads that remain open.

• At-risk buildings and roads likely to close
• Assembly and shelter areas
• Evacuation routes along open roads

Seabed and coastal topography are combined with a wave scenario. The streets the water will reach, the direction of evacuation from the coast to higher ground and the safe assembly areas beyond the wave’s reach are visible in advance.

• Wave scenario and affected coastline
• Evacuation routes to higher ground
• Safe assembly areas

A rainfall scenario is combined with the terrain model; areas where the river may overflow, flooded underpasses and affected buildings are marked. Evacuation routes are drawn around the closed roads, and temporary shelter areas appear on the same map.

• Flood area and at-risk underpasses
• Evacuation routes that remain open
• Temporary shelter areas

The direction of fire spread is animated from wind and building density. The crew dispatched from the nearest fire station, its route to the scene and the nearby hydrants appear on the same map; agencies coordinate in a single view.

• Crew dispatch from the fire station
• Route to the scene and hydrants
• Direction of spread by wind

Regeneration projects are tested in the twin before construction begins. The planned buildings are placed into the existing neighbourhood; their shadow, wind and density effects are visible in advance, and the project is presented to citizens in 3D.

• Planned vs. existing comparison
• Shadow, wind and density effects
• 3D project presentation for citizens

The surroundings of the new buildings are examined in the twin too: air pollution and traffic noise spreading from the avenue are mapped. Layout, façade and green-space decisions are made with these effects in mind.

• Air quality map
• Traffic noise footprint
• Layout and façade decisions

After regeneration, the neighbourhood's infrastructure needs are calculated in the twin too: the water, sewer and electricity load of the new buildings is compared with the existing lines. Undersized lines, the length to be renewed and the cost are known before construction.

• Change in water and electricity demand
• Detection of undersized lines
• Infrastructure renewal cost

Drinking water, sewer, electricity, natural gas and fibre lines become visible below ground together with the structures above. Clashes are caught before excavation begins, and leaks are detected early from pressure and flow data.

• One inventory above and below ground
• Pre-excavation clash analysis
• Locating leaks and faults

Learning models continuously scan the data in the twin, flag anomalies instantly and forecast traffic, energy and maintenance needs in advance. Questions are asked in natural language, and camera footage is analysed automatically.

• Real-time anomaly detection
• Forecast models with confidence intervals
• Natural-language data queries