MotionLeaf: Fine-grained Multi-Leaf Damped Vibration Monitoring for Plant Water Stress using Low-Cost mmWave Sensors

TL;DR

MotionLeaf is a low-cost mmWave sensor system that accurately measures leaf vibrations to monitor plant water stress, offering a novel approach for precise, multi-leaf vibration analysis in plant health assessment.

Contribution

The paper introduces a new mmWave-based system with a signal processing pipeline for fine-grained vibration measurement and stress detection, outperforming existing methods in accuracy.

Findings

Achieves average frequency measurement error of 0.0176 Hz, less than half of prior approaches.

Successfully detects plant water stress during drought experiments using vibration features.

Demonstrates the effectiveness of multi-leaf vibration analysis for plant health monitoring.

Abstract

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.