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| Format: | Recurso digital |
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Zenodo
2026
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| Accès en ligne: | https://doi.org/10.5281/zenodo.18113609 |
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| _version_ | 1866901152839237632 |
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| author | Zorawar Singh |
| author_facet | Zorawar Singh |
| contents | <p>Artificial Intelligence (AI) has emerged as a transformative force across scientific disciplines, with profound implications for environmental science. In this paper, let us explore the multifaceted impact of AI technologies including machine learning, deep learning, computer vision and natural language processing on environmental monitoring, modelling, prediction and policy formulation. AI enhances data processing from satellites, sensors and citizen science platforms, improves the accuracy of climate and ecological forecasts and enables real-time decision-making for conservation and sustainability. Case studies in wildfire prediction, deforestation tracking, and species identification illustrate the practical utility of AI. Integration of AI into environmental science promises more responsive, scalable and equitable environmental governance. This editorial underscores the necessity of interdisciplinary collaboration to maximize the potential of AI while mitigating its ecological and ethical risks.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18113609 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Green Intelligence: Transforming Environmental Science through Artificial Intelligence Zorawar Singh <p>Artificial Intelligence (AI) has emerged as a transformative force across scientific disciplines, with profound implications for environmental science. In this paper, let us explore the multifaceted impact of AI technologies including machine learning, deep learning, computer vision and natural language processing on environmental monitoring, modelling, prediction and policy formulation. AI enhances data processing from satellites, sensors and citizen science platforms, improves the accuracy of climate and ecological forecasts and enables real-time decision-making for conservation and sustainability. Case studies in wildfire prediction, deforestation tracking, and species identification illustrate the practical utility of AI. Integration of AI into environmental science promises more responsive, scalable and equitable environmental governance. This editorial underscores the necessity of interdisciplinary collaboration to maximize the potential of AI while mitigating its ecological and ethical risks.</p> |
| title | Green Intelligence: Transforming Environmental Science through Artificial Intelligence |
| url | https://doi.org/10.5281/zenodo.18113609 |