AI - Driven Predictive Models for Urban Heat Island Mitigation Using Real - Time Environmental Data

Shaik Abdul Kareem

Abstract: Urban Heat Island (UHI) effects pose a significant challenge to public health and urban sustainability. This paper presents an AI - driven predictive model designed to mitigate UHI by leveraging real - time environmental data. The model integrates satellite imagery, weather sensor data, and urban infrastructure information to predict UHI hotspots and propose actionable mitigation strategies. By employing advanced machine learning techniques, including deep learning and spatiotemporal analysis, the model offers a novel approach to addressing UHI. This research demonstrates the model's effectiveness through case studies in several urban areas, highlighting temperature reduction, improved air quality, and recognition from environmental organizations.

Keywords: AI - Driven Predictive Models, Urban Heat Island Mitigation, Real - Time Environmental Data, Climate Change, Urban Climate