Computational Twin

Urban Computational Twins are extremely rare and are the most exciting for us at Spatiomatics. Our SIMO software is based on CAD technology and a unique product offering in relation to the other types of digital twins. I would say that SIMO is probably the only Urban Computational Twin and the only one that provides a standardised Urban Information Model.

SIMO provides computational design workflows that fully integrate into the McNeel software platform of Rhino 3D and Grasshopper 3D. You can integrate all methods of computational design, generative design, evolutionary design and an endless amount of custom project workflows developed in-house by design teams across the globe.

Strengths

• Full control over the design process, generating form, automating tasks, full data-driven design.

• Possibility of advance coding, scripting, and data analysis.

• Speed of design iterations and evolution of the final design.

• Enormous ecosystem of extra tools, plug-ins and workflow optimisations as part of the Grasshopper ecosystem.

• High accuracy of both the geometry and data with access to very powerful computational geometry algorithms.

Weaknesses

• You need to understand how to work with computational design software which adds some extra learning to the process.

• It is more challenging to create a stable data set due to the volatile nature of computational design, but it is possible.

Operational Twin

Urban operational twins tend to be built with either GIS or Gaming technology platforms. Their main purpose is to monitor urban assets in real time based upon Internet of Things (IoT) sensor data overlaid on an urban model. These software are not intended to be modelling, computational or scenario planning tools. They are for the most part management tools for constructed elements. Operational twins are very common in buildings (e.g. manufacturing plants, sports stadia, transport hubs, etc.) and less so for urban environments. They typically contain a lot of information both in terms of geometry and data.

Strengths

Gaming

• High quality representation of models (sunlight, textures, detail).

• Possibility to see the model in VR or AR.

Gis

• Standard workflows based on decades of development.

Weaknesses

Gaming

• The technology was not intended for general purpose use and tends to be overcomplicated. Developing software on

Experiential Twin

Experiential twins are fairly new to the market since they are fully based on gaming technology platforms which have only recently begun repackaging their products for more general use. They are used to create a more ‘realistic’ experience of an urban environment which is especially helpful for stakeholder communication (e.g. communication with a non-technical community affected by a project). Likewise these twins often allow for both VR and AR experience of an urban development. I teach an Urbanism studio at TU Delft where students use VR to design and analyse their projects — it is a fantastic tool. These are very helpful for assessing development and design scenarios (e.g. new streetscape design, density proposals, etc. The image right shows how Amsterdam uses gaming technology. You can zoom into the model and see more detail, depending on twin’s Level of Detail (LOD).

Strengths

• Helpful in creating a ‘feeling’ of the environment if you detail the model.

• Helpful in communicating an urban devel- these technology platforms is challenging.

• The technology is designed for representation and not creation, so it does not support modelling, data management to general users of the software. Skilled technical teams need to build the digital twin and then deploy it for public use.

• No system for data governance, user administration.

Gis

• Legacy systems which make them difficult to modernise to current needs.

• Is not designed for general purpose modelling and data management. Skilled technical teams need to build the digital twin and then deploy it for public use.

• Has limited software providers and Esri has a monopoly on commercial tools and is not known for innovation.

• Difficult to scale to urban areas while maintaining detail and accuracy.

With both gaming and GIS technologies it is challenging to combine diverse data sources, formats and technology standards.

SCREENSHOT OF 3D AMSTERDAM, SOURCE: AUTHOR, GEMEENTE AMSTERDAM opment to non-technical stakeholders.

• Gaming technology is very advanced and develops quickly, so models will become more realistic with time).

Weaknesses

• Difficult to create these models, you need lots of technical expertise.

• Limited data integrations and user interface options for seeing project data or technical analysis.

• The technology is demanding on the computer and the models which are shareable online will have some data restrictions.