Cluster Meeting for Smart Communities Projects in EU, 17 Jun 2022

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Roberto Di Bernardo
Engineering Ingegneria informatica SpA
roberto.dibernardo@eng.it
www.eng.it
Enhanced Urban Planning through
Disruptive Technologies for more Age Friendly Cities

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Europe is getting older…

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Creating age
friendly cities is
an URGENT
policy problem…

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Presenting unique challenges
around health, mobility, and
the physical environment

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Yet urban planning
processes can
struggle to
effectively engage
older people

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Decision Support
Ecosystem
Big Data
Artificial Intelligence
Simulations
New technologies
can help accelerate
a shift towards
more inclusive and
co-created services

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Digital Twin technology provides a virtual representation of the
real world for collaborative decision making

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Research Topics and Challenges
 Adapting urban environments to current challenges requires
a multidisciplinary understanding of interrelated and
complex phenomena.
 In the context of the digital-era massive data production and
enhanced analytical capacities, there is enormous untapped
potential in the use of disruptive technologies to support
evidence-based decision-making processes in the field of
urban planning:
• Artificial intelligence and Big Data analytics
• Urban digital twins
 Risk of excluding vulnerable population; in particular, older
adults, who are less digitally literate and might show distrust
of decisions and engagement based on technology.

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Research Topics and Challenges
 Urban Planning and management in the Smart City era: How do we leverage the power of Big
Data analytics and AI simulation to tackle complexity and facilitate multi-stakeholder decision-
making?
 Age-friendly environments: How do we make sure older people are engaged and decisions help
shape friendlier environments for them?
 Stakeholder engagement in decision-making and technology acceptance: How do we foster
engagement and measure acceptance, considering ethical challenges, while stimulating adoption
of disruptive technologies among public servants and older people?
 Data management: How do we capture, fuse and cure data from various sources?
 Artificial Intelligence - Algorithms & Simulations: What AI Techniques are better suited to
enhance modelling and scenario development for better decision making in urban planning and
management?
 Urban Digital Twin: How do we connect City Information Models to multiple data sources and AI
algorithms to develop scenarios?

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Approach
Urban planning and
management
Data-driven short-term
management and long-term
planning Support Systems, with
simulation capacities and
accessible interfaces to inform
and enable active public
participation in decision making
for age-friendly cities.

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Technology Platform
Urbanage Ecosystem
Platform adopts a secure,
multi module approach:
 Big Data Analytics
 Vizualisations
 Predictive Algorithms
 Artificial Intelligence
 Simulations

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Use cases
Santander
 Accessibility facilities information
 Neighborhood assessment for Land Use Plan review
 No previous digital twin
 Large amount of data from people and city sensors
 Age-friendly route planner, Simulation tool for long-term urban planning
Flanders Region
 Interest in management of obstacles on public areas
 Evaluation of services and equipment for the elderly population
 Previous digital twin of the region (DUET)
 Green comfort, City services planning for older people
Helsinki
 Real-time information provided by citizens, active participation
 Application with accessibility map in real time
 Previous digital twin in the Kalatasama district.
 Feedback on accessibility issues, Point of Interest

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Use cases - Santander
Short-term Medium-long-term,
• tool for civil servants
• improve the age friendliness neighbourhood index of a
specific neighbourhood( urban accessibility, access to
public services….)
• make decision about which are the optimal places to
• install a mechanical ramp or a lift
• specific public infrastructure (civic center, library …)
• public space (parks or green areas) .
MULTI-CRITERIA ANALYSES
DECISION MAKING TOOL
Pilot Case 1: Age friendly router planner Pilot Case 2: Simulation tool for long-term urban planning

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Use cases - Flanders (Use Case 1: Green Comfort Index)
Green Comfort Index score in public domain
 GOAL = Find green & comfortable spots for older people in the
city
• Air quality, noise levels
• Heat stress and shadow maps + 3D visualisation shadow-rich zones
• Green infrastructure (trees)
• Blue infrastructure (water/ponds/rivers)
• POIs (benches, tables, public toilets, street lights)
• Accessibility and reachability (surface, sidewalk quality, reachability)
 TARGET GROUPS
• Policy makers (planning, prioritisation, improve accessibility)
• Older citizens (information, co-creation by app & community building)
• Experts (co-creation by app, simulation & analyses, dissemination (scenarios)

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Use cases – Flanders (Use Case 1: Green Comfort Index)
Tools
 Map viewer, citytwin.eu for 2D & 3D maps
 Feedback app to correct/calibrate GCI
 Gamification, cocreation, dissemination tools
 Artificial intelligence (AI)
1. Map the public domain
2. Measurement/calibration of the GCI + corrections by older citizens and experts +
customised settings + parameter interactions
3. Analysis of orthophotos, satellite data and street view service(s) to recognise POIs in the
landscape.
Roles
• Visitor
• Visitor with login
• Expert with login
• Administration

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Use cases – Flanders (Use Case 2: Service Planning Older People)
Focus on policy makers, city planners, civil
servants
 Creation of a map​
• Age distribution of the population​
• Distribution of people with a reduced mobility​
• Combination of both layers
 Overlay of these maps with existing maps​
• Example, Zorgatlas of Geopunt
 Show combined layers:​
• Where to add new services for older people​
• Where to improve the reachability and accessibility of
existing services + prioritisation?

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Use cases – Helsinki
 Use Case 1: Feedback on accessibility issues
• Where issues occur? What factors affect (active) mobility? →
Better understanding of issues and data for decision making
• e.g., Helsinki accessibility guidelines for 2022-2025 (data
to evaluate the real accessibility)
 Use Case 2: Points of Interest
• Where people move? What routes they prefer? What kinds
of places/environments they enjoy? → Data can be used to
shape existing services and assist with long-term planning and
decision making

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Use cases – Helsinki
 Use Case 3: Travel-time Matrix
• How well does the city work for older
people in terms of accessibility?
• Can they reach the locations of their
everyday activities?
• How does the situation differ
between neighbourhoods, how does it
differ with regards to personal challenges,
requirements, restrictions?​
• What and where should planners focus
on to improve older people’s lives?

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Consortium
 12 partners from 6
European countries with
an excellent
complementary
background
 3 European cities/regions
 3 years project
(02/2021 - 01/2024)

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Thank you!
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