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CLASS Wellbeing Assessment

Neuroscience applied to urban green design.

Urban renovation isn’t just about energy efficiency; it’s about people. The Contemplative Landscape Automated Scoring System (CLASS), developed by NeuroLandscape, introduces a groundbreaking neuroscientific approach to urban planning. It is designed to evaluate the quality of urban green spaces and their potential to reduce stress and improve mental health.

Using AI models trained on brain-response data, CLASS analyzes images of parks, streets, and public squares. It assigns a “contemplative score” to each view, predicting its therapeutic value for citizens. This ensures that BLUEPRINT renovations contribute to a healthier, more restorative urban environment, aligning with the “Beautiful” and “Inclusive” pillars of the New European Bauhaus.

Lead partners

Technology Readiness Level (TRL)

TRL7 (System Prototype Demonstration)

Primary domain

Neuroscience & Urban Health

Key Technology Components (TCs)

CLASS AI Scoring Algorithm: The core engine evaluating visual landscape quality.

Mental Health Impact Indicator: metrics linking design features to stress reduction.

Visual Pattern Analysis: Automated detection of restorative elements (water, vegetation, depth).

Users

Landscape Architects

Public Health Officers

Urban Designers