In this paper, an RFID coupled batteryless digital sensor tag is proposed for detecting Ammonia in packaged food. An interdigitated capacitive sensor coated with a thin film of Polyaniline(PANi) that has a higher affinity towards Ammonia is used as a sensing element. To determining the sensitivity of the sensing element, (i) Wireless Near field Short range technique (Capacitance change), and (ii) Direct Probing (Resistance change) techniques are evaluated. The short range technique consists of an inductor coupled to the interdigitated capacitor to form an LC tank and the resonance (capacitance) change due to Ammonia loading is read using a pick-up coil. The direct probe technique uses two wires to measure the resistance across the interdigitated capacitor as a function of Ammonia concentration. Among the two techniques, for demonstrating long range sensing with digitization, direct probing is chosen as this is more stable and can detect a minimum of 3 ppm of Ammonia at room temperature with a response time of 30 min and recovery time of 60 min. The long range approach consists of an RF front end with an antenna and an energy harvester and a low power digital backend that converts the sensor data into bits for transmission. The entire system is passive in nature and does not require an external power supply for operation making it a low cost and simple solution that can be easily integrated as part of the RFID infrastructure. The ID integrated sensor tags are used for a myriad of quality control applications across the food supply chain spectrum.

Harmonic Radio Frequency Identification (RFID) systems have attracted significant interest over the last decade as it provides many benefits over the conventional RFID systems. Harmonic RFID is desired over conventional RFID systems due to reduced self-jamming, location accuracy from dual frequency, and higher phase noise immunity. In a harmonic RFID system, the tag receives instructions from the reader at an RF carrier frequency and replies back at the harmonic of the RF frequency. A nonlinear element consuming very low power at the tag is required to generate the harmonic carrier for the battery-less system. In this review article, a detailed contrast between conventional and harmonic RFID systems is presented. This is followed by different circuit design techniques to generate harmonics and integration techniques to form a fully operable passive harmonic RFID tag. Also, a wide range of applications, especially sensor integration with harmonic RFID’s, along with the future trends are presented.

In this paper, a harmonic RFID (hRFID) system is proposed to overcome the challenges that limits the capabilities of a conventional UHF RFID system such as self-jamming and multi-path interference without any extensive modifications to the existing infrastructure. The proposed system exploits the third harmonic generation from the existing RFID chips for communication. The system is realized by designing an additional RF interface layer between the conventional RFID interrogator and the RFID tag. The interface layer transmits the query signal at the fundamental frequency and receives the backscattered harmonic signal from the RFID tag. It down converts the backscattered third harmonic signal to the fundamental frequency, and feeds it back to the conventional UHF interrogator for extracting the information. A dual band antenna design is also shown for improving the radiation efficiency of hRFID tags using a conventional RFID ICs with improved signal to noise ratio (SNR) and increased read range. A path is shown for improving the hRFID system by performing a study that relates the read range, RFID IC’s sensitivity, and the noise level with efficiency. The proposed system can be easily adapted to any of the current RFID applications.

In this letter, a single-antenna-based compact harmonic RFID tag having efficient power harvesting topology is demonstrated. The harmonic RFID receives a continuous signal at the fundamental frequency (fo = 434 MHz) and replies back with modulation at the second harmonic (2fo = 868 MHz). To enhance the read range, the harmonic RFID tag topology was designed to harvest energy simultaneously while performing modulation in a continuous mode. Furthermore, the harmonic RFID allows the use of lower modulation rates to reduce power consumption, thus further enhancing the read range. Performance at different modulation rates is demonstrated. Overall, a compact and efficient harmonic RFID is demonstrated with a read range of 8 m at a 1-kHz tag data modulation rate and 30-dBm transmit power.

We develop a high-Q capacitive sensing based robust non-destructive evaluation (NDE) methodology that can be widely used in varied NDE applications. We show that the proposed method can detect defects in a host of robust regimes where uncertainties such as lift-off, probe tilt, fluctuations in sampling rates, and step sizes are inherent in the data collection process. We explicitly characterize the corruption in the capacitive sensing data due to various lift-off based uncertainties. We use a Bayesian decision theoretic approach to rigorously understand the impact of these corruptions on defect identification efficacy. Using an optimally tuned weighted classification loss, we prove that it is theoretically feasible to accurately detect defect location and sizes from capacitive sensing signals collected under the aforementioned uncertainties. The Bayesian decision theoretic study needs prior information for accurate detection that is not available in real NDE inspections. So, we develop a solely data driven algorithm that analyzes the capacitive sensing signals without any prior knowledge of defect or uncertainty types. The developed algorithm is non-parametric and uses spatially adaptive denoising to weed out uncertainty induced noises. By leveraging the spatial association in the capacitive sensing signals, our algorithm greatly improves on popular non-spatial approaches. Compared to popular thresholding methods and low-rank based denoising approaches, we demonstrate superior performance of the proposed method in terms of coverage and false positive metrics for defect identification. Using spatially adaptive denoising, we design a robust capacitive sensing method that can detect defects with high precision under various uncertainty regimes.