气体检测中的人工智能:一篇评论
M A Z Chowdhury1, M A Oehlschlaeger1
1Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, New York 12180, United States.
ACS sensors
|March 11, 2025
概括
人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 通过提高准确性和快速检测来增强气体传感. 这些人工智能方法可以创建适应性传感器系统,用于各种应用,如环境监测和医学诊断.
科学领域:
- 材料科学 材料科学 材料科学
- 计算机科学 计算机科学
- 化学 化学 化学
背景情况:
- 气体传感技术对于各种应用至关重要,包括环境监测,工业安全和医疗诊断.
- 传统的气体传感器经常面临准确性,选择性和处理复杂数据的能力方面的挑战.
- 新兴的智能气体传感器系统需要先进的数据处理和解释能力.
研究的目的:
- 审查人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 在增强气体传感方法中的作用.
- 探索AI,ML和DL对新兴气体传感器系统的发展的影响.
- 突出将AI与气体传感器技术集成的方法.
主要方法:
- 在气体传感中对AI,ML和DL应用的现有文献的审查.
- 对传感器信号的AI驱动数据处理技术的分析.
- 检查AI算法和气体传感器硬件之间的集成策略.
主要成果:
- AI,ML和DL显著提高了气体检测的准确性,灵敏性和选择性.
- 这些方法可以快速检测气体,并进行定量度测量.
- 人工智能有助于开发可适应,交叉敏感的传感器系统,以在各种条件下进行多重检测.
结论:
- 人工智能在气体传感器技术中的整合代表了范式的转变,导致了前所未有的性能.
- 由人工智能驱动的气体传感器为环境监测,工业安全,遥感和医疗诊断提供了改进的能力.
- 对人工智能传感器集成的进一步研究将推动智能气体传感系统的发展.
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