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金属污染 - 全球环境问题:来源,影响和缓解方面的进展

Gabrijel Ondrasek¹, Jonti Shepherd¹, Santosha Rathod²

¹Faculty of Agriculture, The University of Zagreb 10000 Zagreb Croatia gondrasek@agr.hr.

|February 12, 2025

概括

金属污染对健康和生态系统构成风险. 人工智能 (AI) 与传感器相结合,可以改善对金属污染的检测和管理,以及环境清洁的植物修复策略.

科学领域:

环境科学环境科学
生物技术是生物技术.
数据科学数据科学数据科学

背景情况:

金属污染 (MC) 是一个不断升级的全球环境问题,通过各种暴露途径影响人类健康和生态系统.
工业化和人口增长正在加剧与MC相关的风险,需要先进的补救和监测解决方案.
现有的基于生物的修复方法,如植物提取,显示出希望,但在复杂的环境场景中面临挑战.

研究的目的:

探索人工智能 (AI) 在解决金属污染检测和管理的复杂性方面的潜力.
研究人工智能与先进的传感器技术的整合,以加强植物修复策略.
要突出跨学科的方法,以可持续地减轻金属污染的影响.

主要方法:

对金属植物进行系统选,以寻找有效的植物修复候选物.
应用人工智能 (AI) 算法来建模金属生物的生长和活动.
整合人工智能与先进的传感器技术和基于现场的试验.

主要成果:

人工智能算法为建模复杂的金属环境相互作用和管理金属生物提供了强大的工具.
人工智能和传感器技术的结合可以改善金属污染的检测和预测.
人工智能可以帮助填补了解不同污染环境中的金属菌有效性的知识差距.

结论:

人工智能为彻底改变金属污染补救策略提供了变革的潜力.
结合人工智能,传感器和现场试验的跨学科方法对于有效和可持续的环境清洁至关重要.
结合这些技术的未来研究可以显著减轻金属污染的有害影响.

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