flanders

Flanders is a network of interrelated cities forming together with Brussels a large metropolis area. Flanders alone can be considered as one single, smart region of 6.7 million people. The Smart Flanders network brings the region together to create the necessary scale for smart city solution- and data providers. A Flanders Digital Twin will play a crucial role to open and democratise available Smart City data to citizens, companies and service providers to use for co-created policy and age-friendly services.

Flanders wishes to extend its knowledge of local digital twins for evidence based decision making for more age-friendly infrastructure and services by combining geo and social data for more intelligent insights. A series of interactive co-creation workshops with older residents and stakeholders helped define the use case scenarios and subsequent solution development.

Flanders Demo: The Green Comfort Index Use Case

Demo of the URBANAGE capabilities in the city of Ghent

A series of meetings and workshop were organised. Twelve potential interesting high-impact scenarios, spread over 6 themes (health & wellbeing, physical accessibility, social experience, living and mobility) were defined and refined as a starting point. Twelve scenarios meeting the needs as addressed by field experts and being in line with the overall Urbanage philosophy. During a first workshop, the twelve pre-set scenarios were presented, explained and discussed with representatives of the five selected central cities. As a result of the workshop, three scenarios were selected as most relevant. (1) The heat stress scenario:, (2) The scenario of city services planning for older people; (3) The scenario of the introduction of a mobility score for older people. After extensive internal analysis of the quality of available expertise & datasets and of feasibility of the roll-out, it was decided to only continue with the two first scenarios. Both scenarios were worked out and concretised (based on personas) during a second Miro interactive workshop with the city representatives. This resulted in two well-defined cases. Also, a first fit-gap analysis exercise of desirable and available local and governmental datasets was done. Finally, the two withheld mature cases were presented to the representatives of the older people community. Valuable feedback was gained and processed to optimise some aspects of both cases. The most important update is the broadening and redefinition of the heat stress case to a green comfort case.

Co-creation Outcomes

Expected Benefits

Working with personal data is always a legal challenge. The result of the selected use cases is a legal framework for data aggregation and automatic rights allocation. Based on data and algorithms, we want to investigate how we can support decision processes. We want this both for the current situation and for long-term urban planning. An important added value of the use case is the end-to-end approach. We translate the needs of the citizen into data and then into algorithms. Finally, we examine how we can get the result back to the citizen.