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基于智能CO2传感器网络的野火预警系统
Alessio De Rango1, Luca Furnari1, Fabio Cortale1
1Department of Environmental Engineering, University of Calabria, Rende, 87036 Cosenza, Italy.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
一个新的智能二氧化碳 (CO2) 传感器网络与人工智能 (AI) 模型显著改善了野火早期检测. 这种由人工智能驱动的系统比传统方法更快地激活更多的传感器,帮助消防工作.
科学领域:
- 环境科学 环境科学
- 计算机科学 计算机科学
- 风险管理 风险管理
背景情况:
- 气候变化加剧了野火风险,特别是在地中海等容易干旱的地区.
- 有效的野火管理需要先进的战略和技术整合.
- 早期检测对于减轻野火损害和支持应对行动至关重要.
研究的目的:
- 提出和评估一个智能二氧化碳 (CO2) 传感器网络,用于野火早期预警.
- 开发和比较人工智能 (AI) 模型,以使用二氧化碳数据增强火灾检测.
- 评估系统在现实环境中的有效性及其对灭火的支持.
主要方法:
- 部署一个通过云平台连接的二氧化碳传感器网络,用于数据管理.
- 开发了三种人工智能模型:自动编码器 (AEs) 和长短记忆器 (LSTM).
- 与44个传感器的受控野火实验中基于非AI值模型的AI模型的比较.
主要成果:
- 人工智能模型,特别是LSTM,与非人工智能模型相比,从二氧化碳数据中提取了更有价值的信息.
- 人工智能系统在更短的时间内激活了多达56%的传感器.
- 该系统成功地追踪了风力模式影响的潜在火线传播.
结论:
- 拟议的智能二氧化碳传感器网络与人工智能显著提高了早期野火检测能力.
- 人工智能模型改善了传感器数据的分析,从而导致更快,更全面的警报.
- 这项技术为改善野火风险管理和支持消防行动提供了有价值的工具.
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