MotionLeaf: Fine-grained Multi-Leaf Damped Vibration Monitoring for Plant Water Stress using Low-Cost mmWave Sensors
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866917795218849792 |
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| author | Cardamis, Mark Chou, Chun Tung Hu, Wen |
| author_facet | Cardamis, Mark Chou, Chun Tung Hu, Wen |
| contents | In this paper, we introduce MotionLeaf , a novel mmWave base multi-point vibration frequency measurement system that can estimate plant stress by analyzing the surface vibrations of multiple leaves. MotionLeaf features a novel signal processing pipeline that accurately estimates fine-grained damped vibration frequencies based on noisy micro-displacement measurements from a mmWave radar. Specifically we explore the Interquartile Mean (IQM) of coherent phase differences from neighboring Frequency-Modulated Continuous Wave (FMCW) radar chirps to calculate micro-displacements. Furthermore, we use the measurements from multiple received antennas in the radar to estimate the vibration signals of different leaves via a Blind Source Separation (BSS) method. Experimental results demonstrate that MotionLeaf can accurately measure the frequency of multiple leaves in a plant with average error of 0.0176 Hz, which is less than 50% of that (0.0416 Hz) of the state-of-the-art approach (mmVib). Additionally, the estimated natural vibration frequencies from MotionLeaf are shown to be an excellent feature to detect the water stress in the plant during 7-day drought experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_03679 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MotionLeaf: Fine-grained Multi-Leaf Damped Vibration Monitoring for Plant Water Stress using Low-Cost mmWave Sensors Cardamis, Mark Chou, Chun Tung Hu, Wen Signal Processing In this paper, we introduce MotionLeaf , a novel mmWave base multi-point vibration frequency measurement system that can estimate plant stress by analyzing the surface vibrations of multiple leaves. MotionLeaf features a novel signal processing pipeline that accurately estimates fine-grained damped vibration frequencies based on noisy micro-displacement measurements from a mmWave radar. Specifically we explore the Interquartile Mean (IQM) of coherent phase differences from neighboring Frequency-Modulated Continuous Wave (FMCW) radar chirps to calculate micro-displacements. Furthermore, we use the measurements from multiple received antennas in the radar to estimate the vibration signals of different leaves via a Blind Source Separation (BSS) method. Experimental results demonstrate that MotionLeaf can accurately measure the frequency of multiple leaves in a plant with average error of 0.0176 Hz, which is less than 50% of that (0.0416 Hz) of the state-of-the-art approach (mmVib). Additionally, the estimated natural vibration frequencies from MotionLeaf are shown to be an excellent feature to detect the water stress in the plant during 7-day drought experiments. |
| title | MotionLeaf: Fine-grained Multi-Leaf Damped Vibration Monitoring for Plant Water Stress using Low-Cost mmWave Sensors |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2410.03679 |