资源有限环境中的地理信息系统

arXiv - CS - Computers and Society Pub Date : 2024-08-30 DOI:arxiv-2408.17361

Marc Böhlen, Gede Sughiarta, Atiek Kurnianingsih, Srikar Reddy Gopaladinne, Sujay Shrivastava, Hemanth Kumar Reddy Gorla

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引用次数: 0

摘要

本文介绍了空间感知人工智能（GeoAI），它是为非政府组织等小型组织量身定制的，这些组织在资源有限的情况下可能难以获得大型数据集、昂贵的计算基础设施和人工智能专业知识。此外，我们还考虑了资源密集型大型地理空间模型可能会使复杂地貌的表达同质化的未来情景，并提出了应对这种情况的策略。

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GeoAI in resource-constrained environments

This paper describes spatially aware Artificial Intelligence, GeoAI, tailored for small organizations such as NGOs in resource constrained contexts where access to large datasets, expensive compute infrastructure and AI expertise may be restricted. We furthermore consider future scenarios in which resource-intensive, large geospatial models may homogenize the representation of complex landscapes, and suggest strategies to prepare for this condition.

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arXiv - CS - Computers and Society

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