Question 1

How can local digital twins be extended to refine a district’s profile representation, guiding PED design and demonstrators?

Accepted Answer

Quantitative measurements of a city, such as sensor data and measurements, are more easily collected and therefore widely used on PEDs and DT development. However, qualitative data such as the citizens' perceptions and feelings represent an important set of information regarding the inhabited environment that is currently not integrated into traditional or standardized PED developments, limiting the complete and correct representation of the dynamics that condition the sustainability of a region. With this in mind, the BIPED project focuses on the development of novel methodologies that collect this “soft data”, to include it into the models and analysis run in the digital twin.

Question 2

How can the quantitative collection of soft data support the advancement in digital twin development?

Accepted Answer

PEDs districts are traditionally designed from an isolated point of view, leaving aside multiple correlations and connections with other districts and other larger scale territories (e.g. city), resulting in a weak replication of its dynamics and components that consequently hamper the cooperation of different city levels and administrative entities, challenging the implementation of strategies towards the ultimate goal of climate neutral cities. The collection and integration of “soft data” into the analysis aims to create a more accurate and complete representation of the true dynamics of the district in the digital twin, including qualitative components that are often overlooked in traditional urban planning methodologies.

Question 3

How to boost the replication potential of PED solutions for climate neutral cities and communities with reinforced decision-makings?

Accepted Answer

To address the barriers previously identified and capture the full panorama of the district of Brabrand in Aarhus, Denmark, the BIPED project proposes and develops a holistic approach where important social and economic variables are included as part of the baseline components of the model. This approach initiates the development of an interoperable extended local digital twin (BIPED digital twin), with a structure that allows for seamless escalation and replication in other districts and regions.

The BIPED approach