On the feasibility of estimating soluble sugar content using millimeter-wave

Abstract

With the development of novel sensing techniques, continuous monitoring, data-driven inferences, precision irrigation control, and intelligent Internet-of-Things (IoT) systems, agriculture sector is witnessing a revolution. Specialized devices based on infrared and laser are developed to assist farmers in assessing the produce quality, especially its sugar content. However, such devices are expensive and not readily available to consumers. In this paper, we investigate the feasibility of using 60 GHz millimeter-wave (mmWave) signal as a ubiquitous and non-invasive way to estimate the Soluble Sugar Content (SSC) in fruits. With the rapid development in the mmWave technology, 60 GHz WiFi is likely to become pervasive in future mobile devices. Our study shows that when 60 GHz WiFi signals reflect from a fruit, the reflection can be used to infer the fruit's sugar content. We identify the underlying reasons of variations in reflection signals with varying SSC and study the impact of size, shape and density of fruits on reflections. We then develop statistical features based on received signal strength and amplitude, and use them to design regression-based estimation models. With an extensive evaluation with 300 fruit samples, we find that our proposed technique can estimate SSC in three different type of fruits with an average correlation coefficient of 85%. Our prediction errors are within the range of user's taste perception.

SSCense

“…This is due to the spacing between the antennas and the curved shape of the objects, the reflected signals captured from different antennas could be distinct and vary in strength. So, relying on a single antenna pair, as in a previous study [1], is not suitable for SSC estimation.…”

“…Estimating SSC Using mmWave Reflection: When SSC increases in an aqueous solution, the number of free water molecules drops, and the permittivity of the solution decreases [1]; so, the RSS of the reflection from that solution should also decrease. To observe the relationship between RSS and permittivity, we conduct controlled experiments by varying the sugar content inside a container with water, placing it in front of the mmWave device (Fig.…”

“…Our preliminary experiments show that SSCense can estimate the SSC with an average error of less than 0.58 • Bx for controlled sugar solutions and less than 1.43 • Bx for real fruits. Moreover, we show that a prior approach using a single antenna for estimating the SSC [1] performs poorly in a practical environment, and our multi-antenna mmWave transceiver based design promises hand-held estimation of SSC in fruits.…”

SING: Free-Space SensING of Grape Moisture Using RF Shadowing

“…The effect of RF signals on plants has been discussed in previous research [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]. More specifically, the effect of RF signals on the moisture content, the density, and/or the sugar concentration -to name a few -have been investigated for different fruits and vegetables [6], [7], [8], [11], [14], [15], [16].…”

Automatic Temperature Measurement and Monitoring System for Milling Process of AA6041 Aluminum Aloy using MLX90614 Infrared Thermometer Sensor with Arduino

“…Arduino has also been widely used in various fields including medicine [13] such as to develop heart rate and body temperature monitoring system [14], heart diseases, diabetes etc. It was also applied in power systems such as plantations thermal generator [15], crop health monitoring and household devices [16].…”