MINDCity

This solution helps municipalities and organizations go digital and manage their data effectively on a local level.

It is a key tool for smart cities, energy planning, adapting to climate change, and making decisions about urban retrofitting

What does it do? It checks out urban KPIs for buildings and helps planning for energy transition and climate change adaptation:

• City microclimate model (100x100m)

• Rates how buildings are vulnerable to climate issues

• Forecasts energy retrofitting and climate adaptation strategies

• Sends heat wave communications—4 days ahead

• Supports designing urban green spaces and shelters

Description

BEEMind tools : MindCity

                 High resilient cities in practice

BEEMind tools : MindCity

• Integration, processing, and visualization of large amounts of urban data at the building level

• AI powered models to improve cities and make them more resilient against extreme weather events.

• Figuring out specific geospatial indicators that connect to climate action and shift towards cleaner energy.

• Evaluation of greening and urban climate adaptation scenarios

Funcionalities

Cities 4.0: Environmentally Smart

• Facilitates strategic decision-making in the energy, climate, and urban planning fields

• Optimizes resources and processes for large-scale city data analysis

• Improves coordination between technical departments and citizen interaction

• Highly scalable to any city in Europe

Benefits

BEEMind tools : MindCity

Use cases

• Optimizes resources and processes
  For large-scale analysis of geo referenced urban data

• Improves coordination
  Between municipal technical departments and citizen interaction

• Scalability

  ​Straightforward for most Spanish cities

        Adaptable to other EU cities as long as data are

        available

• Climate Vulnerability map
  Detect buildings where people might be under climate vulnerability based on cross-sectional analysis of KPIs.

• Support buildings energy retrofitting
  Identify and prioritize buildings with the greatest demands and higher retrofitting potential.

• Actions to adapt to climate disruptions
  Optimizing climate shelters location, better climate communications with citizens, estimate greening and shadowing areas potential...

Impacts

Cities 4.0: Environmentally Smart

BEEMind tools : MindCity

More precision

Current development

Case Study: Climate Vulnerability Map of Barcelona

Vulnerability map:  Climate-Ready BCN

Source: ICLEI Action Fund 2.0
Budget: €1M
Objective: Support citizens and public authorities in adapting to extreme climate events and reducing energy poverty
Implemented: From May 2023 to March 2026

Vulnerability map:  Climate-Ready BCN

Climate Vulnerability in Barcelona at building level

The Climate Vulnerability Map of Barcelona is a geospatial analysis tool designed to identify the buildings most at risk during extreme heat events.

It evaluates key performance indicators (KPIs) for buildings and supports climate change planning

It provides an assessment of all residential buildings in Barcelona (61,000)

What is it?

CVI

How we estimate the Climate Vulnerability Index (CVI)

Vulnerability index to asses heat wave resilience

Climate vulnerability is typically framed within three key dimensions defined in the IPCC's Third Assessment Report (Intergovernmental Panel on Climate Change) in 2001:

Exposure
Sensitivity
Adaptive capacity

Although most studies classify indicators using these three categories, our index introduces additional levels to provide a more nuanced analysis while remaining aligned with the traditional framework.

 Climate vulnerability Index (CVI)

1. Data preprocessing – Select input data to calculate the indicators.

2. Framework selection – Determine which indicators positively or negatively affect the CVI.

3. Granularity definition – Select the spatial scale.

4. Normalization & weighting – Harmonize indicators and assign weights.

5. Aggregation – Combine indicators into groups to obtain a final value.

⚠️ Challenge: Each study adapts its CVI to its specific context and priorities.

CVI Construction

Vulnerability map

Climate variability and extreme events

• Track changes over time through indicators such as temperature, precipitation, and vegetation cover. Local data helps assess risks related to heatwaves, droughts, and floods.

Energy indicators

• Explore energy use patterns (gas and electricity consumption). Indoor temperature data is crucial for identifying households at risk during extreme heat events.

Building characteristics

• Assess features such as age, use, and size to understand their impact on energy use, indoor comfort, and structural vulnerability.

Indicators groups (KPIs)

Vulnerability map

Indicators groups (KPIs)

Vulnerability map

Infrastructure indicators
Assess the availability of essential public services (schools, climate shelters, social housing) and the strength of social networks to understand community support capacity.

Health indicators
Analyze the relationship between climate and health outcomes to identify vulnerable populations and prepare healthcare systems.

Demographic indicators
Not all groups are equally vulnerable. Analyzing factors such as gender, age, income, migration status, and unemployment allows for the development of more detailed CVIs.

Socioeconomic indicators
Understand urban resilience through factors such as housing costs, energy poverty, household debt, and gaps in social protection, which worsen during economic crises.

Modelos de colaboración

MindCity

Modelos de colaboración

Vulnerability map

Qué es MindCity?

• Motor de análisis urbano basado en modelos científicos

• Evaluación edificio a edificio

• Índice de vulnerabilidad climática

• Modelos de redes neuronales para demanda energética

• Simulación microclimática urbana

• Prospección masiva de energía fotovoltaica

• Escenarios de adaptación y transición energética

Conceptualización

• Motor científico de inteligencia climática y energética urbana

• Enfoque basado en interoperabilidad y gobernanza pública

• Integración con plataforma comercial

Modelos de colaboración

Motor científico público + plataforma de explotación urbana escalable.

Posicionamiento estratégico

• Motor científico validado

• Infraestructura de datos interoperable

• Plataforma de generación de conocimiento

• Soporte a decisiones públicas estructurales

• Desarrollo e investigación continua

• Plataforma transversal multi-dominio

• Experiencia en integración de datos heterogéneos

• Capacidad de despliegue comercial en ciudades

• Interfaz orientada a múltiples perfiles (técnicos, políticos, ciudadanía)

• Escalabilidad operativa y soporte continuo

Arquitectura de colaboración

Motor científico (centro público)

• Índice de vulnerabilidad climática

• Modelos de redes neuronales

• Simulación energética masiva

• Modelización microclimática

• Prospección fotovoltaica avanzada

• Modelo semántico interoperable

• Integración transversal de dominios urbanos

• Visualización geoespacial avanzada

• Portal ciudadano y cuadro de mando político

• Integración con sistemas municipales

• APIs abiertas

• Capacidad de despliegue internacional

Plataforma Urbana
(privada)

Arquitectura de colaboración

Propuesta

Motor científico

• Modelos predictivos

• Índice de vulnerabilidad

• Simulación energética

• Modelización microclimática

• Estructura semántica de datos

• Visualización

• Interfaz multi-actor

• Portal ciudadano

• Integración municipal

• Comercialización

Plataforma comercial

Modelo hacia cliente final

Propuesta

Motor científico

• Modelos predictivos

• Índice de vulnerabilidad

• Simulación energética

• Modelización microclimática

• Estructura semántica de datos

• Visualización

• Interfaz multi-actor

• Portal ciudadano

• Integración municipal

• Comercialización

Plataforma comercial

Framework para colaboración público-privada

Capas de valor

Objetivos

• Modelo semántico

• Estructura de indicadores

• Librerías base

• Esquema de cálculo general

• Interoperabilidad

• Cumplimiento con misión pública

• Credibilidad europea

Capa A - Framework abierto

Capa B - Inteligencia como servicio

• Pesos entrenados de redes neuronales

• Ajustes microclimáticos calibrados

• Curvas de sensibilidad específicas

• Factores de corrección por tipología urbana

• Ajustes dinámicos por contexto climático

• Actualización anual oficial del índice

• Publicación institucional

• Validación científica periódica

• Versión certificada

Capa C - Gobernanza y actualizaciones