Wi-Wheat+: Contact-free wheat moisture sensing with commodity WiFi based on entropy

Abstract

In this paper, we propose a contact-free wheat moisture monitoring system, termed Wi-Wheat+, to address the several limitations of the existing grain moisture detection technologies, such as time-consuming process, expensive equipment, low accuracy, and difficulty in real-time monitoring. The proposed system is based on Commodity WiFi and is easy to deploy. Leveraging WiFi CSI data, this paper proposes a feature extraction method based on multi-scale and multi-channel entropy. The feasibility and stability of the system are validated through experiments in both Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) scenarios, where ten types of wheat moisture content are tested using multi-class Support Vector Machine (SVM). Compared with the Wi-Wheat system proposed in our prior work, Wi-Wheat+ ​has higher efficiency, requiring only a simple training process, and can sense more wheat moisture content levels.

Keywords

• Channel state information (CSI)
• WiFi
• Multi-scale entropy
• Multi-class support vector machine (SVM)
• Radio frequency (RF) sensing