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AI Climate Toolkit for Predictive Analytics, Risk Mitigation, Ecosystem Restoration, and Sustainable Urban Future
Abstract
Background: Some of the problems due to climate change are high temperatures, flooding, and pollution within urban centers. To enhance sustainable urban development, AI Climate Toolkit addresses these through risk reduction, ecosystem restoration, and predictive analytics. Methods: In terms of maximizing resources, reduction of hazards, and the preservation of biodiversity, it employs a combination of datasets and maps, Internet of Things sensors, and machine learning in its toolkit. Results: The toolkit's ability to enhance the resiliency of urban climate was evident from the prediction accuracy of 0.05°C, carbon sequestration of 2.2 kg/m2, and policy compliance at 93%. The toolbox offers a way to sustainable growth of the urban area, even though scale and equity remain challenges.
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