ELEVATE exemplifies transdisciplinary research by combining academic methods with lived experiences. ELEVATE’s innovation pathway comprises five integrated core WPs.

WP1 — Co-creation & stakeholder engagement

This work package focuses on participatory co-creation with residents, planners, public health experts, and stakeholders. Through workshops and focus groups, ELEVATE identifies the environmental qualities that support healthy and active living and ensures that research outcomes remain grounded in real-world needs and experiences.

Main activities:

  • Stakeholder mapping
  • Co-creation workshops
  • Focus groups
  • Citizen engagement
  • User-centered evaluation

WP2 — Smartphone-based mobility & physical activity assessment

This work package collects high-resolution mobility and walking-related physical activity data using smartphones, GPS tracking, and accelerometry.

Main activities:

  • GPS tracking
  • Step-count assessment
  • Survey data collection
  • Mobility analysis
  • Data quality and validation

WP3 — AI-based streetscape & environmental analysis

This work package develops detailed environmental indicators using street view imagery, GIS, and artificial intelligence methods.

Main activities:

  • Street view image analysis
  • Computer vision
  • Deep learning
  • Streetscape perception analysis
  • Environmental exposure assessment

WP4 — Qualitative & mixed-methods research

This work package investigates how people experience and perceive urban environments in daily life.

Main activities:

  • Walk-along interviews
  • On-site qualitative inquiry
  • Thematic analysis
  • Integration of qualitative and quantitative findings

WP5 — Spatial modeling & data integration

This work package examines how environmental exposures are associated with walking-related physical activity patterns.

Main activities:

  • Spatiotemporal clustering
  • Statistical modeling
  • Machine learning
  • Equity analysis
  • Exposure assessment

WP6 — AI recommender system for urban design

This work package develops an AI-powered recommender system that translates research findings into practical urban (re)design recommendations.

Main activities:

  • AI model development
  • Urban design recommendations
  • Explainable AI
  • Interactive web interface
  • Stakeholder evaluation

WP7 — Dissemination, open science & impact

This work package ensures that findings, tools, and knowledge are translated into societal impact.

Main activities:

  • Publications
  • Policy translation
  • Open science
  • Public outreach
  • Demonstration sessions
  • Knowledge exchange