Public & DefenseDigital Twin & Smart City Platform
TwinUp
TwinUp is a digital twin platform that brings a city's assets, systems and processes into one virtual model fed by live data. GIS, BIM, infrastructure inventories and IoT data meet in the same model, and disaster, planning and operations scenarios are simulated before decisions are made. AI modules extract crowd density, road defects and shop signs from camera and 360° street imagery.
Highlights
- Scenario analysis: see the impact of planned investments and possible disasters in advance
- Real-time impact modelling: simulate traffic, infrastructure and environmental change
- Integrated management: above- and below-ground data on one platform
- Faster decisions from reports built on simulation results
- Density, anomaly and road-defect detection from camera footage, with person and vehicle counts
- Signage inventory: detection, reading and m² measurement from 360° street imagery, validated against LiDAR
- City modelling from LOD 0 to 500, starting with a pilot area
Video
Watch TwinUp
A city's digital twin, with its layers and scenarios.
Scenarios
Simulation before the decision
Disasters, plans and field operations are tried on the same city model before they happen.
- 01
Disaster management
For a possible earthquake, it uses building permits and building ages to find the buildings at risk, the bridges and viaducts likely to close and the fastest route for rescue teams, in advance.
- Flood: flooding areas and infrastructure capacity
- Fire: spread speed and direction from wind data, fire-brigade response time
- Snow: routes for gritting and snow-plough vehicles
- 02
Smart city planning
It simulates the traffic, infrastructure and social impact of a new shopping centre, metro line or urban-renewal project before construction, and compares the options on cost and efficiency.
- Public transport: lines and frequencies by passenger demand
- 15-minute city: access maps for health, education and parks
- Cycle-lane routes
- The air-quality effect of low-emission zones and gas conversion
- 03
Operational efficiency
Before digging, underground infrastructure is shown on site in augmented reality (AR), preventing damage to pipes and cables and service outages. Fault and maintenance work is run from the centre.
Data
The city's data in one model
Above- and below-ground data meet in the same digital twin, and the city's management systems connect with live data.
Layers
- Live data streams (IoT)
- Real-time data from sensors and devices
- Building information modelling (BIM)
- Buildings' geometry and information
- Infrastructure inventories
- Water, energy and other network lines
- Geographic information systems (GIS)
- Map, parcels and road network
Connected systems
- Public transport management
- Smart traffic systems
- Parking management
- City cameras
- Smart waste management
- Smart metering
- Public Wi-Fi points
- Environmental sensors
Automation
Automation and image analysis
Rules tied to sensor data adjust city services on their own, and AI processes footage from city and vehicle cameras.
Smart city automation
- Smart irrigation
- Parks are watered by soil-moisture sensors, so no water is wasted.
- Smart lighting
- Street lights dim to pedestrian and traffic density, cutting energy costs.
- Traffic signals
- Signal timings follow live traffic density, so traffic flows better.
- Water-leak detection
- A pressure anomaly opens a work order for the right crew automatically.
Detection from imagery
- Density
- Live crowd density in open spaces
- Anomalies
- Abandoned packages, illegal dumping
- Road defects
- Automatic detection of potholes and cracks
- Counting
- Person and vehicle counts for predictive analysis
- Signage inventory
- Sign detection, reading and measurement from 360° street imagery (try it below)
Public & Defense
Signage inventory module
A demo running on synthetic data. It holds no real customer data and works fully by keyboard.
Getting started
A transformation that starts with a pilot area
Instead of the whole city, it starts with one area; once the value is proven on a concrete problem, the model grows.
- 01
Choosing a strategic area
A critical neighbourhood, industrial zone or urban-renewal area is chosen as the pilot.
- 02
Modelling and data integration
The area's digital twin is built from existing GIS, BIM and infrastructure data, and live data sources are connected.
- 03
Scenario analysis
Scenarios are run on a priority problem, such as flood risk or congestion, so the platform's value is seen in concrete terms.
- LOD 02D polygon
- LOD 100Massing model
- LOD 200Form, size and facade
- LOD 300Exact size and geometry
- LOD 400Fabrication and assembly
- LOD 500Matches the site (as-built)
The city is modelled at the level the project needs and its budget allows, from simple massing to engineering detail.
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