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Completed COLLABORATIVE R&D UKRI Gateway to Research

Urban Heat Sensing: Mitigating, and adapting to, heat-related climate risks by empowering citizens via Assistive AI and Next Generation Digital Twins

£752.3K GBP

Funder Innovate UK
Recipient Organization Dark Matter Laboratories Limited
Country United Kingdom
Start Date Jun 30, 2024
End Date Feb 28, 2025
Duration 243 days
Data Source UKRI Gateway to Research
Grant ID 10117045
Grant Description

Cities are increasingly at risk of heatwave events, with over 30% of the world's population exposed to life-threatening heat extremes for more than 20 days per year. A study in Seoul found an 8.4% increase in total mortality during heat waves. Green infrastructure and Nature-based Solutions (NBS) are crucial in mitigating the urban heat island effect.

By strategically incorporating vegetation and natural/ low-energy cooling mechanisms, cities can drive thermal comfort while delivering multiple benefits.

To enhance decision-making capabilities, cities are increasingly utilising digital twins to simulate and predict the potential impacts of urban interventions. However, one of the main challenges is the comprehensive collection and integration of relevant data. This not only encompasses the physical and environmental data but also requires a deep understanding of social dynamics, including the community's preferences, needs, and values.

Gathering data that accurately reflects what people care about ensures that the simulations are grounded in the reality of residents' lives, making the outcomes of these digital twins more relevant and actionable. However, data collection is not enough; we must also explore how to transform these data points into insight and action.

Therefore, the feasibility study will look into

1. Localising a risk-based vulnerability assessment: we will develop a data framework that streamlines various remote, weather, institutional, and citizen stories and sensing to assess the climate risks of heat island effects in cities and support the creation of community engagement strategies.

2. Assistive AI and civic participatory tools to broaden the audience of services to the general public: we will use generative AI to run different adaptation and mitigation scenarios from individual to institutional levels to assess the potential cooling effect of a broad spectrum of interventions - providing easy to understand personalised recommendations, complete with rationale and references.

The foundational technological and social elements established in Phase 1 will be the basis for the next development phase. In Phase 2, we envision developing social permission and stewardship contracts regarding peer-to-peer and micro-actions, such as creating small gardens, sharing cooling shelters, and painting with reflective paints. These are critical pathways to implementing large-scale policy interventions around climate adaptation and mitigation strategies.

Risk management is equally essential for landscape-level interventions by governments and individual citizens, with aggregate resilience capacities at the city scale.

This will allow us to see the potential to apply them to other disaster management contexts, such as flooding, food crises, urban safety, and public health/pandemics.

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