在环境监测中整合人工智能:数据驱动的可持续发展的范式转变
Ufondu Maryann Afoma1, Shilpy Singh1, Abhishek Kumar Mishra1
1Department of Biotechnology & Microbiology, School of Sciences, Noida International University, Greater Noida, Gautam Budh Nagar, Uttar Pradesh, India.
EcoHealth
|August 28, 2025
概括
人工智能 (AI) 通过自动化数据收集和分析来彻底改变环境监测. 人工智能工具增强生物多样性努力和可持续管理,克服传统方法的局限性.
科学领域:
- 环境科学
- 生态学
- 计算机科学
背景情况:
- 传统的环境监测方法往往耗费大量资源,难以扩展.
- 越来越多的人类影响需要先进,高效的监测解决方案.
- 人工智能提供自动数据收集,实时分析和预测能力.
研究的目的:
- 审查人工智能环境监测方面的进展.
- 突出人工智能在空气/水质,气候和生物多样性的应用.
- 讨论人工智能在生态管理中的挑战和战略.
主要方法:
- 审查当前的人工智能技术,包括机器学习 (ML) 和深度学习 (DL).
- 使用无人机图像,摄像头陷和GPS数据探索人工智能应用.
- 强调新兴技术,如可解释的人工智能 (XAI),边缘计算和物联网 (IoT).
主要成果:
- 人工智能可以实现自动数据收集,实时分析和环境监测的预测建模.
- 人工智能应用包括物种识别,息地评估,野生动物追踪和反偷猎工作.
- 像XAI,边缘计算和物联网这样的新兴技术提高了人工智能模型的透明度并降低了成本.
结论:
- 人工智能对于可持续的环境管理和生态管理具有变革性的潜力.
- 解决数据质量,计算需求和模型可解释性等挑战至关重要.
- 跨学科战略,道德框架和政策调整是成功整合人工智能的关键.
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