Accessibility issues and needs that were identified
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providing means for older adults to participate in urban planning;
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solve accessibility/mobility issues by collecting, visualising and sharing relevant, up to date and area specific data to inform decision making;
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create datasets of interesting and enjoyable places to assist in future planning efforts;
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measuring travel-time in Helsinki region considering needs of older citizens.
Solutions to these needs will be piloted with the following three use cases:
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feedback on accessibility issues - piloted in Vuosaari
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point of Interest - piloted in Vuosaari
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travel-Time Matrix - piloted in the whole metropolitan area
Accessibility issues and needs that were identified
-
providing means for older adults to participate in urban planning;
-
solve accessibility/mobility issues by collecting, visualising and sharing relevant, up to date and area specific data to inform decision making;
-
create datasets of interesting and enjoyable places to assist in future planning efforts;
-
measuring travel-time in Helsinki region considering needs of older citizens.
Solutions to these needs will be piloted with the following three use cases:
-
feedback on accessibility issues - piloted in Vuosaari
-
point of Interest - piloted in Vuosaari
-
travel-Time Matrix - piloted in the whole metropolitan area
technology approach
architecture. integration. platform
technology approach
flanders
Background info
The population pyramid of the Flemish Region in 2019 shows the characteristic profile of an outdated population: a heavy peak and a narrow base. The category “50 to 64-year-old” weighs heavily in the population. It is therefore crucial that public services are tailored to the needs of this ever-growing but also evolving target group. Next to the inverted age pyramid, the problem of urban sprawling between the Flanders major cities causes specific problems in terms of equal accessibility of public services for vulnerable groups such as older people, today and tomorrow.
Problems to solve
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.
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The heat stress scenario;
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The scenario of city services planning for older people;
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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.
Why Urbanage solution?
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Policymakers will be supported in their policy towards older people and evolving populations in neighborhoods through data-based evidence, unlocked by combining geo and social data.
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Citizens may receive proactive notifications and report nuisances to increase the accuracy of the nuisance prediction algorithms.
expected benefits
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Working with personal data is always a legal challenge. The result of this use case is a legal framework for data aggregation and automatic rights allocation.
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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.
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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.
