Urban Heat Islands

Project description

Research question:
How can ai be used to effectively monitor urban heat islands in Eindhoven, to predict and mitigate health risks, thereby enhancing public safety?

This project aims to develop a machine learning model for the Safety and Security Campus (SSC) in Eindhoven, focusing on urban heat islands (UHIs), where elevated temperatures pose significant public health risks. The tool uses open-source data collection and predictive modelling to identify high-risk zones, analyse historical temperature patterns, and assess mitigation strategies. By addressing challenges such as GDPR compliance and resource constraints, the project aims to provide local officials with actionable insights to proactively manage heat-related hazards. Leveraging data on vegetation, building density, and water bodies, the tool will enable targeted interventions to reduce health emergencies during extreme heat events. This research serves as a proof of concept, showcasing the potential for technology to enhance urban safety, support sustainable city planning, etc.

Context

Urban heat islands (UHIs), where city areas experience higher temperatures than their surroundings, pose significant public health risks, especially as climate change intensifies heatwaves. Vulnerable populations face increased risks of heat-related illnesses, including heatstroke and dehydration.

Results

The main result of our project is that we do not have the right data to make any useful predictions.