基于单个传感器的超低功率电子鼻子系统,由任务循环和深度学习为实时气体识别提供动力
Taejung Kim1, Yonggi Kim2, Wootaek Cho1
1Department of Mechanical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.
ACS sensors
|June 10, 2024
概括
这项研究引入了一种超低功率的电子鼻子,使用单个传感器和工作循环来有效识别气体. 这种新的系统显著降低了电力消耗,使得物联网的长期监控成为可能.
科学领域:
- 材料科学 材料科学 材料科学
- 传感器技术 传感器技术
- 人工智能的人工智能
背景情况:
- 传统的电子鼻子 (e-nose) 系统通常依赖于传感器阵列,导致功耗和成本增加.
- 金属氧化物半导体 (MOS) 传感器广泛用于气体检测,但可能耗电.
研究的目的:
- 开发一种新的超低功率单传感器电子鼻子系统,用于实时气体识别.
- 为了减少实际物联网应用的e-nose技术的电力需求.
主要方法:
- 在一个悬浮的1D纳米加热器上使用单个MOS传感器,由工作循环 (脉冲功率) 驱动.
- 利用传感器对解温度和表面电荷效应的超快速热反应.
- 使用卷积神经网络进行气体识别和度回归.
主要成果:
- 在30秒内实现了五种气体类型的早期识别,分类准确率为93.9%.
- 显示了高达90%的显著功率降低,达到160微瓦.
- 获得了19.8%的度回归误差.
结论:
- 单传感器电子鼻子系统有效地识别高精度和最低功耗的气体.
- 该技术可通过晶圆级批量工艺制造,使成本效益高,电池驱动的物联网监控成为可能.
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