Time-Transient Wireless RF Sensor With Differentiative Detection Capability in Ionic Aqueous Environment for Water Conservation and Green Cleaning

Autor: Sobhan Gholami, Emre Unal, Hilmi Volkan Demir
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Journal of Microwaves, Vol 4, Iss 4, Pp 1001-1008 (2024)
Druh dokumentu: article
ISSN: 2692-8388
DOI: 10.1109/JMW.2024.3484754
Popis: A novel wireless microstrip-based RF sensor designed for detecting changes in the ionic content of water and the addition of solid contaminant objects is proposed and demonstrated for the purpose of water conservation and green cleaning. The sensor can be installed on the exterior wall of dielectric containers and customized according to the material of the container (such as porcelain) to enable wireless sensing inside the container. Its operation within the lower microwave frequency range (670–730 MHz) serves to minimize signal attenuation in water and streamline circuitry design. The most significant feature of this sensor is its unique design, rendering it impervious to its surrounding environment. This not only shields it from environmental noise but also maximizes its sensitivity by efficiently utilizing incoming power for sensing purposes. The sensor exhibits remarkable sensitivity, capable of detecting solute concentrations as low as 3.125 $ \times$ 10-3 M in water inside the container. It can also detect the insertion of foreign solid objects into the container from the exterior wirelessly and distinguish them from liquids being added. As a proof-of-concept demonstration, the sensor in this study was built for a porcelain wall of 10-12 mm thickness. The sensor's small size and the materials used for its fabrication make it an ideal choice for various smart bathroom applications, where accurate and reliable water use monitoring is essential for efficient water conservation and green cleaning. The sensor's ability to distinguish between the added solid objects and liquid electrolytes in the container provides the necessary sensing data for running water-saving and efficient washing mechanisms in bathrooms.
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