Remote Identification of Liquids Using Absorbent Materials: A Passive UHF RFID-Based Method
Remote characterization of liquids can be beneficial in various industry sectors such as food and oil industries, medical diagnostics, agriculture, or waste management. However, current wireless solutions are often expensive and labor-intensive. Antenna-based sensors (ABSs) can potentially decrease the complexity and cost of current solutions. Ultrahigh-frequency (UHF) radio frequency identification (RFID) sensors for liquid characterization have the potential to provide remote monitoring while fulfilling the previous requirements. This work demonstrates the combined effects of the dielectric properties on the operation of RFID-based sensors and it presents an innovative approach for estimating the dielectric properties of a liquid under test (LUT) from the read range peak frequency and magnitude variations of a UHF RFID tag. The tag antenna consists of a patch-like antenna with an absorbent embedded into its substrate. Filling the absorbent with different LUTs modifies the dielectric properties of the substrate which has a measurable effect on the tag read range. Measurements show that the proposed method together with the specific sensor design enables the dielectric characterization of liquids using an energy-efficient and low-cost solution achieving an accuracy over 93.5% and 84% in the estimation of the LUT relative permittivity and the loss tangent, respectively, compared to the transmission line (TL) method.
Passive Sensing for the Internet of Medical Things: A Low-Cost Battery-Less Wearable Sweat Rate Sensor
Continuous monitoring of the sweat rate can support the early diagnosis of several chronic diseases such as Parkinson’s or diabetes. However, current wearable wireless devices use batteries that have a limited operating time, also increasing their cost, and thus, reducing their accessibility to a large part of the population. In that sense, passive IoT technologies could be exploited to produce battery-less low-cost antenna-based sensors (ABS). In this paper, we propose a UHF RFID battery-less antenna-based sensor that transforms the amount of sweat accumulated inside a microfluidic channel into a variation of the tag response. In order to provide multi-level sensing, we rely on the IC self-tuning sensor code, which is passively backscattered to the reader unit, instead of channel information which may provide insufficient resolution depending on the geographical location. The sensor performance is validated experimentally, achieving an accuracy of 90% in the estimation of the sweat loss and 95% in the estimation of the average sweat rate.
A Battery-Less and Low-Cost RFID Sensor for Unassisted Multilevel Detection of Sweat Loss
Emerging applications for wearable sweat loss measuring devices (SLMD) require real-time and long-term operation. These applications impose strict constraints to SLMD in terms of power consumption, size, and flexibility. Several efforts have been made to avoid battery limitations in electronic sensors. However, this remains an open challenge. This contribution presents a battery-less wireless data transfer device enabling sweat loss monitoring through a wearable, flexible, and low-profile antenna-based sensor (ABS). The proposed sensor design includes a small piece of fabric embedded in the antenna substrate to absorb sweat secreted by the skin in contact with the sensor inlet interface. This novel feature dramatically improves the frequency selectivity and frequency range of the ABS in response to the contact with liquids, which increases the measurement accuracy in comparison to the current state of the art, enabling real-time multilevel sweat loss detection. The sensor performance is assessed using a commercial radio frequency identification (RFID) system through laboratory and real-life experiments. The results show that the proposed sensor can track sweat loss within the typical range of the human perspiration rate (300–2100 g/m2/h) of healthy individuals using a battery-less and low-cost sensor.
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