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Green AI for Climate Risk Prediction and Environmental Monitoring

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£120.00 £114.00 £116.40 £118.80 £121.20 £123.60 £126.00 25 September 2026 26 September 2026 27 September 2026 28 September 2026 29 September 2026
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Description

This comprehensive guide explores how Green AI technology transforms climate risk management through advanced machine learning and data analytics. The book examines practical applications of sustainable artificial intelligence in weather forecasting, natural disaster prediction, and biodiversity monitoring, drawing on satellite data, sensor networks, and atmospheric analysis. Designed for scientists, policymakers, and environmental professionals, it presents proven strategies for using AI-driven models to forecast extreme weather events, assess environmental vulnerabilities, and make informed decisions that mitigate the impact of floods, droughts, wildfires, and other climate threats. Published by Engineering Science Reference, this resource bridges the gap between cutting-edge AI technology and real-world climate adaptation, offering actionable insights for building resilient communities and protecting natural ecosystems in an era of accelerating environmental change.

Key Features

Green AI methods for processing satellite, sensor, and atmospheric data to enable accurate climate pattern monitoring and environmental risk assessment.

Practical frameworks for using machine learning models to forecast extreme weather events and predict natural disasters with improved accuracy.

Strategies for applying AI-driven analysis to biodiversity monitoring and ecosystem health evaluation across diverse environmental contexts.

Guidance for scientists, policymakers, and communities to make informed decisions that reduce the impact of climate threats on vulnerable populations.

Sustainable artificial intelligence approaches that balance computational efficiency with environmental protection objectives.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
16 April 2026
Listed Since
20 April 2026

Barcode

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