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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 an AI built on a large language model (LLM) pipeline and neurophysiological responses, CLASS analyzes images of parks, streets, and public squares.

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