Radio-frequency identification (RFID) technology has helped grow the Internet of Things (IoT) by being integrated in sensing, localizing, and tracking applications. To help increase the read-range of a passive or semi-passive RFID tag, this research proposes a preliminary design for a retrodirective, tunneling RFID tag architecture that loads a rat-race coupler with reflection amplifiers made out of low-power tunnel diodes. By banking a small amount of power to drive this circuitry (216 microwatts), a backscattered signal can be boosted by 18 dB and the read range by a factor of around 3.

ZeroScatter BLE is an all-digital, fully synthesizable approach for adding Bluetooth Low Energy (BLE) backscatter wireless data uplinks to existing field-programmable gate arrays (FPGAs). Unlike conventional FPGA-based BLE devices that require an external BLE chipset in addition to the FPGA, ZeroScatter BLE is fully synthesizable from Verilog register transfer language (RTL) code. This allows ZeroScatter BLE to be be implemented on billions of existing FPGAs. A tri-state capable digital I/O pin, a stable digital clock that's divisible to 1 MHz, and a 2.4 GHz antenna connected directly to the FPGA I/O pin are required to form the BLE backscatter device. An external carrier source in the 2.4 GHz band is then backscatter modulated with a BLE subcarrier using the two distinct RF impedances formed by the FPGA I/O pin direction switching between logic-zero and tri-state.

Our experimental setup includes a signal generator serving as a 2.4 GHz carrier wave (CW) source. This CW source is backscattered by an antenna attached to a Lattice iCE40 FPGA running the ZeroScatter BLE logic. The resulting BLE backscatter signal is then received by an unmodified iOS or Android device using a commercial BLE scanner app. With a CW carrier power of +30 dBm, we have verified a bistatic range exceeding 4 m in a multipath-rich indoor environment, using an unmodified iPad as the BLE receiver. This work points the way toward wireless communications links created entirely from commodity digital logic.

Efficient energy harvesting is crucial for the seamless operation of passive UHF RFID sensor applications, especially in energy-constrained environments. We present a novel approach to optimize RFID transponder energy harvesting using a carefully designed charge pump system. We pump energy from the transponder's rectified supply voltage to a storage capacitor from which we power the EEPROM and sensors. By regulating the rectifier output voltage, i.e. the input of the charge pump, the maximum energy is extracted without overloading the rectifier. Compared to conventional charge pump output voltage regulation, our approach maintains a minimum supply for the operation of the transponder IC. Our implementation using an analog control loop with a voltage controlled oscillator results in a lower ripple of the rectifier voltage compared to a digital control loop. The entire design is implemented and validated in a commercial 180-nm CMOS technology.

This paper introduces a new method allowing one to improve the delta RCS of any passive transponder. We show that the delta RCS associated to the proposed technique can be higher than the one predicted by the equation of R. Green in 1963. By switching simultaneously the loads connected to a dual-port antenna, we show analytically that the delta RCS of the dual-port tag can be improved by 6 dB. This improvement corresponds to an increase of the round-trip read range of 41%. This result can still be improved if the modulation of the structural mode adds constructively with the modulation of the antenna mode. Simulation and measurement of a dual-port tag based on two independent UHF tags validate the model and achieve a large part of the predicted improvement.

Radio Frequency Identification (RFID) is often used in high tag density scenarios where tag read rate becomes a limiting factor. Current Class 1 Gen 2 (C1G2) RFID systems are limited in read rate by the Framed Slotted Aloha (FSA) scheduling algorithm and physical layer modulation parameters. We propose a multi-user MIMO (MU-MIMO) RFID system compatible with C1G2 which is capable of communicating with more than one tag simultaneously allowing greater read rates. Multiple reader receiver antennas are exploited to recover collided tag data and perform channel estimation. The channel estimates are used to precode the reader ACK signals from multiple transmit antennas into spatial channels so that the tags will receive fully separated acknowledgements. An experiment is carried out using two monostatic transceivers with two emulated tags, showing successful channel recoveries and uncollided reader acknowledgments commands at the tags.

Over the past few decades, the utilization of Radio Frequency Identification (RFID) technology has expanded across multiple domains, such as inventory control, intelligent charging systems, passive sensing, and localization services. This study introduces an innovative deployment of RFID in smart antenna systems, particularly focusing on the wireless remote control of the radiation pattern of a Yagi-Uda antenna through Ultra High Frequency (UHF) RFID technology. Our unique method employs RFID to remotely change the length of the passive resonator, allowing it to serve as either a director or a reflector. This approach effectively overcomes the limitations of wire-based control seen in traditional pattern-configurable antennas, ensuring stable antenna patterns while minimizing both cost and energy expenditure. The proposed Yagi antenna demonstrates directional operation at 2.4 GHz and achieves a gain of approximately 5.6 dBi with an impressive front-to-back ratio of 10.6 dB. Additionally, the system showcases high energy efficiency, with power consumption reaching only 12 uW.

This work studies device-free localization (DFL) of static humans in a room. Contrary to data-driven techniques, no training data is required, but instead, measurements of the room with or without people are only needed, using a minimal number of RFID reader antennas and a large number of passive RFID tags. A phase-based method based on group sparsity, coupled with RF propagation, is proposed, as well as a practical method to fuse results from independent DFL techniques. Numerical results show that the fusion scheme of independent DFL methods, based on signal strength and phase offers improved performance.

We present a method for passive wireless channel estimation in RF tag-to-tag link. The technique has a low computational complexity, a small memory footprint and requires only one additional port in the modulator design of RF tag. The performance of the proposed method is evaluated on distance estimation task. The performance in the range of tag-to-tag dis- tance from 28 cm to 228 cm is limited to 10o. The demonstrated performance is comparable to performance of distance estimation techniques based on RFID technology which utilize RFID reader and are not scalable as the proposed method. The proposed method is amenable to deployment in near zero power operation RF-powered tags and it enriches RF tags with the ability to passively ‘fingerprint' their surrounding.

We present RL2, a robotic system for efficient and accurate localization of UHF RFID tags. In contrast to past robotic RFID localization systems, which have mostly focused on location accuracy, RL2 learns how to jointly optimize the accuracy and speed of localization. To do so, it introduces a reinforcement-learning-based (RL) trajectory optimization network that learns the next best trajectory for a robot-mounted reader antenna. Our algorithm encodes the aperture length and location confidence (using a synthetic-aperture-radar formulation) from multiple RFID tags into the state observations and uses them to learn the optimal trajectory. We built an end-to-end prototype of RL2 with an antenna moving on a ceiling-mounted 2D robotic track. We evaluated RL2 and demonstrated that with the median 3D localization accuracy of 0.55m, it locates multiple RFID tags 2.13x faster compared to a baseline strategy. Our results show the potential for RL-based RFID localization to enhance the efficiency of RFID inventory processes in areas spanning manufacturing, retail, and logistics.

Logistics management has emerged as a key component to human activities conducted in space or remote habitations in general. The RFID Enabled Autonomous Logistics Management (REALM) system has played a key role in providing cargo tracking capabilities in the complex RF scattering environment in the ISS. Currently, the inferencing engines used by REALM to predict the location of RFID tagged items operate on an hour of data,. Whereas many movements of interest aboard the ISS occurs on the scale of seconds. In this work, we propose a new inferencing engine that produces an embedding space to represent the location of RFID marked cargo on the scale of 30 seconds to 2 minutes of data, allowing for the categorization of movement of cargo and predictions of a coarse location in less time than existing REALM engines employed to date.

The implementation of ultra-wide band (UWB) systems in a facility enables the real-time tracking of asset locations. However, commercial off-the-shelf UWB software applications for real-time tracking only include top-down 2D projections of the environment and represent the active tags as simple dots, which are not adjusted to reflect the size of the object the tag is attached to. This representation may be sufficient for simple implementations but does not adequately portray the location of tags in relation to other objects in a spatially intuitive manner. The present work exhibits an application that provides users with an interactive 3D photorealistic environment to view UWB tagged assets. In the application, users can virtually "walk" through the facility to observe and interact with tagged assets to obtain information about the asset and its movements. Additionally, the location data is filtered to improve the visualization so that users can make meaningful interpretations about the trajectory of the tagged objects. This software will be useful in many scenarios, such as asset tracking demonstrations, facility monitoring, and process management.

We propose a dual-channel Dickson rectifier including two independent 1-stage rectifiers for the radio frequency (RF) energy harvesting sensors. It presents the characteristic model of the native NMOS and the leakage model of the Dickson rectifier. The power consumption model of the switch and charging time are derived. Further, 1-stage rectifiers with NMOS W/L=2μm/1μm and W/L=16μm/1μm are designed to work in the rectifier input power Prec_in smaller and larger than -18 dBm, respectively. The maximum power conversion efficiency (PCE) are 63.84% and 63.92% in the two ranges. The size of the PMOS switch for charging the 1nF storage capacitor Cstore is optimized as 100μm/180nm to minimize the power loss.

In this work, we extend the platform presented in [1] by implementing the access commands defined by the RFID protocol (EPC Gen2 [2]). By only modifying the firmware of the micro-controller, any access commands can now be implemented in real time by this simple reader. Two examples are provided based on Read and Write commands allowing any hobbyist to respectfully read and write the memory of the tag in any bank and at any address.

Far-field wireless power transfer (WPT) provides a solution for meeting the increasing demand for accessible and efficient power by allowing power to be delivered without the need for batteries or physical connections. To maximize the amount of power transferred, directional power-beaming transmitters need to have knowledge on the location of the receivers. A pilot beam sent from a WPT receiver to the power-beaming transmitter can properly guide the beam and minimize power loss due to misalignment. This work proposes a retrodirective, power beaming transmitter capable of continuously tracking the phase and frequency of a pilot beam in a narrowband monostatic configuration. The proposed full-duplex design is enabled by the use of a perfect pulse (PP) waveform pilot beam to avoid interference between the pilot and power beams.

Commercial Radio Frequency Identification (RFID) systems have demonstrated a reliable performance for inventory automation and tracking of assets in several industry contexts. However, their feasibility and performance in complex nuclear environments is widely unknown. The ability of RFID systems to properly perform in these environments can be highly affected by multipath propagation problems created by reflective elements, reducing the reliable reading of tags affixed to nuclear material metal enclosures. Thus, understand the physical limits of these antenna devices for automated inventory is a crucial step to select the appropriate RFID tag antennas and methods for tag attachment to achieve reliable and high-performance inventory and tracking systems. In this work, we explore the applicability of finite element method solvers to simulate the dynamics of ultra-high-frequency (UHF) commercial off-the-shelf RFID components to create radio-frequency transport models on different timescales to study the performance of antenna tag matching in simulated nuclear environments. Our goals are to determine how to affix tags to nuclear material containers to maximize the likelihood of tag matching. Also, we aim at characterizing the robustness of these tag antennas to frequency detuning effects potentially caused by the number of metallic surfaces present in these environments. We use a 3D electromagnetic simulation software to verify frequency responses in terms of antenna radiation and scattering patterns, evaluate how much power is reflected and the coupling between different elements in complex nuclear environments with multiple metallic enclosures. The ultimate goal is to precisely define a set of design requirements for RFID tag antennas that could allow to a proper use in the tracking of metallic containers for nuclear material accountability.

The bi-static architecture for backscatter communication offers extended communication range compared to the mono-static architecture due to the disaggregated illuminator and receiver. In this work, we explore the scalability of a bi-static backscatter network (BN) with unsynchronized illuminator and receiver. We consider a bi-static BN with fully asynchronous unslotted random access for reading tags. We introduce "tag drop rate" (TDR) as a metric to analyze network scalability. Furthermore, we define a collision zone parameter to quantify the relationship between collisions and packet corruption and derive an expression for TDR as a function of network parameters and the collision zone parameters. We then design an experimental testbed to estimate the collision zone parameter. Using the estimated value of the parameter, we use numerical analysis to show that with a modest bit-error-rate (BER) requirement, the network can achieve low TDR even with a large number of tags.

Radio-frequency identification (RFID) tags, as radio markers pre-embedded in creep-prone points, can be used for structural health monitoring, due to its low cost, small form factor, extreme durability, no maintenance requirement and passive backscatter communication scheme. Although prior works demonstrated millimeter-precision 3D tag localization inside building materials, they required many known reference points, which is inconvenient for practical deployment. We investigate effects of reduced reference points to localization performance and propose strategies to maintain high precision with seriously degraded fitting accuracy of phase-distance relations in complex near-field channel conditions. By avoiding excessive ambiguity removal at the early stage and exploiting channel spatial diversity more intelligently, three strategies are proposed with only 5% reference points. Millimeter accuracy was validated on Universal Software Radio Peripheral (USRP) devices and second harmonic RFID tags.

This poster demonstrates the design, characterization, and range-analysis of a retrodirective tunneling radio-frequency identification (RFID) tag that utilizes a rat-race coupler loaded with tunnel-diode based reflection amplifiers. By biasing these amplifiers with a small amount of DC power (216 µW), a backscattered signal can be amplified by 18 dB and experience a theoretical improvement in read-range by a factor of around 3 when compared with a tag that uses an open/short load modulation.

Power harvesting efficiency has been the main con- straint of passive radio frequency identification (RFID) tags. The use of power-optimized waveforms (POWs) instead of continuous waveforms (CWs) as the interrogating signals takes advantage of the signals' higher peak-to-average-power ratio (PAPR) and the tags' charge pumps non-linear behavior to extend read-range. To test these POWs, a psuedo-RFID reader has been created with a Software Defined Radio (SDR) with an open-source POW- generation software to facilitate the generation and transmission of POWs to next-generation RFID tags with newer chips, the Impinj M750 and NXP U9.

This poster explores the development and testing of RFID (Radio-Frequency Identification) readers specifically designed for integration with Unmanned Aerial Vehicles (UAVs) or drones. Comprehensive performance evaluations are presented, including range assessments, data acquisition speed, and reliability in dynamic flight conditions. The findings provide valuable insights into the feasibility and effectiveness of RFID technology in aerial applications, opening new avenues for enhanced asset tracking, surveillance, and monitoring capabilities in diverse industries.

Internet of Things (IoT) networks in the 5th and 6th generation (5G/6G) are expected to achieve sensing and low-power communication simultaneously. For integrated sensing and backscatter communication (ISABC), this paper proposes side-channel sensing as a promising approach, which uses the main channel of the backscattered signal for regular communication and simultaneously uses the side channel to transport the sensing information Ψ back to the base station (BS) for processing. We propose a structure of the node's backscatter module to maintain stable communication and extract Ψ separately from the side channel while removing other environmental effects. The modulating impedance can select a reference impedance to offer a stable channel state for communication or a Ψ-dependent impedance to map Ψ into the side channel for sensing. The side channel's power variation and phase shift are used to carry Ψ, which are susceptible to path variation (PV), such as unknown BS-node distance and orientation. We perform a differential calculation for PV cancelling using different side-channel states. Based on the proposed structure, a Gen2-compatible side-channel sensing system has been designed with a liquid-level tag sensor prototype. Experimental results show the effectiveness of our proposed structure in keeping stable communication. Meanwhile, the robustness-test results under different PVs have proved the PV-cancelling validity, showing the standard deviations for the amplitude and phase variations of 0.00325 and 1.67°.

In the realm of securing resource-constrained embedded systems like RFID tags and the Internet of Things (IoT), lightweight cryptography plays a pivotal role. This paper presents a pioneering data transmission system that merges two Physical Unclonable Functions (PUFs) with Ascon, effectively bolstering the security of transmitted data. Tailored explicitly for resource-constrained IoT devices, this system offers a notable advancement in key security by leveraging the integration of PUFs. A significant advantage of this architecture lies in the fortified key security achieved through PUF integration. This eliminates the necessity of transmitting keys over potentially insecure channels, as keys can be derived directly on the device side, capitalizing on the inherent characteristics of PUFs. In practical FPGA implementation, the system demonstrates impressive performance metrics. On the Artix-7 chip, hardware utilization metrics reveal a mere 5.8% utilization of Look-Up Tables (LUT) and a mere 1.9% utilization of Flip-Flops. This innovative approach presents a promising solution tailored specifically for resource-constrained IoT devices, marking a significant stride in enhancing RFID security.

For use in home automation cooling and heating a sensor unit embedded in the floor is required to wirelessly transmit humidity and temperature information. The proposed design fulfills all spatial requirements while still retaining a greater than 80% radiation efficiency combined with an enhanced directivity of 8 dBi to further increase energy and information transmission. The operational bandwidth ranges from 902 MHz to 928 MHz.

Nanobubbles (NBs) suspended in liquid solutions have multiple applications within aerospace life-support systems such as energy-efficient water treatment systems and biological algae generating reactors. The analysis of NBs in constrained environments using radio frequency identification methods, such as CubeSats, presents numerous challenges due to limited space and power availability. An innovative approach to monitor NBs is presented in this work which is based on the change in frequency of a dynamic light scattering system as compared to radio frequency based systems. In addition, RF-based systems are compared with optical systems for monitoring NBs, demonstrating their advantages and limitations. Power consumption, cost, and size of the proposed system are optimized, while achieving an acceptable characterization. In addition, detailed discussions are provided on the key components of our novel CubeSat system.

Environmental monitoring systems has grown exceedingly in recent years due to the effects of global warming. These systems can be implemented by various types of systems including remote sensing systems and Wireless Sensor Networks. This work is focused on close sensing systems for collecting various types of data including soil moisture from the woods. These systems deploy numerous sensors across large regions. As the number of sensors increases, it becomes essential to minimize power consump- tion and implementation costs. The variable cost of implementation refers to the gain and bandwidth of the power amplifiers increasing the gain and therefore coverage area of each node, the required number of nodes will change and decreasing gain will result in less coverage and more nodes for the full coverage. This study focuses on developing a new method to determine the optimal transmitted power and cell size using realistic propagation models for near-ground sensors. The cell coverage based on different chan- nel models is calculated and the result of that is fed to the power cost optimization algorithm. The output of the algorithm contains the optimum number of nodes and required transmitted power concerning receiver sensitivity and near-ground wireless channels. The main objective of this research is to design a low-cost environmental monitoring system that can cover a particular area with a minimum number of sensor nodes. The proposed optimization algorithm is tested under real-world conditions in the Maine forests to assess its experimental performance as well.

This research presents a new variant of direct sequence spread spectrum - Perfect Pulse Direct Sequence Spread Spectrum (PP-DSSS) - that is a generalized, versatile signaling methodology which enables superior communications in the presence of strong, in-band interference signals. Quantitative performance of PP DSSS is compared to a conventional DSSS signaling method, demonstrating an increase of over 25 dB of processing gain for in-band interferers and an additional 13 dB margin in permissible SIR to achieve uncoded BER thresholds. These results promise significant gains for RFID backscatter, dynamic spectrum coexistence schemes, ambient scatter communications, and other advanced wireless communication techniques.

Localizing objects and determining their accurate position and orientation at considerable distances within densely cluttered environments poses a formidable challenge. In this paper, the authors introduce a new approach utilizing ultra- low-power frequency-divided backscatter beams on a single tag to enable azimuth estimation. The reported mm-wave system leverages a cross-polarizing Rotman lens and radar system for its implementation. The details of the system-from the tags baseband and mm-wave front end to the properties of the radar- are presented and its multi-spectral and random-forest data processing methods are described, before the results of its testing in high clutter environments are presented and discussed. These findings underscore the tag's ability to achieve precise localization over more than 10m of range with a median error of 6.4 cm, while also accurately determining orientation with a mean absolute error of 3.6 degree. This work not only addresses the pressing challenge of object localization and orientation detection but also lays a foundation for future advancements in extended-range sensing technology.

This work presents a comparison between RFID and BLE regarding tag localization accuracy under static conditions, where both the antennas and the tag remain stationary. The comparison utilizes a hyperbolic localization technique based on phase differences, which introduces linear approximations of hyperbolas to calculate 3D direction of arrival (DoA) and estimate the tag's 3D position. However, this technique is highly sensitive to multipath noise. The spatial and frequency diversity in BLE aids in mitigating multipath issues, resulting in accurate estimations. In contrast, RFID lacks compatibility with such diversity. This comparison motivates the exploration of developing new algorithms that ensure consistent results for both technologies. Additionally, it suggests the possibility of merging BLE and RFID technologies into a single tag, minimizing energy consumption while also providing accurate localization estimates in static scenarios.

Road markings play a critical role in ensuring road safety and guiding drivers, particularly in adverse weather conditions where visibility is compromised. However, traditional detection methods using cameras and LiDARs often struggle to accurately detect road markings in such conditions. Factors like rain, fog, dust, and snow can obstruct camera views and interfere with the LiDAR's ability to capture thin or faded markings, compromising their effectiveness. In contrast, radar technology offers a promising potential in recognizing these markers even in severe weather conditions and at long ranges, provided they are engineered to retrodirect the radar signal effectively. In this work, a low-cost, low-profile mmWave retroreflective surface that is capable of retrodirecting the signals emanating from an automotive radar was designed and tested. The structure relies on a 78.5 GHz Yagi Uda Van Atta reflectarray that was demonstrated to achieve a measured median RCS of -30 dBsm over a wide angular coverage of 80 degree. The surface was also tested with respect to range, demonstrating a detection distance of 11 m. The proposed architecture was finally simulated in a stacked configuration showcasing its potential to achieve larger RCSs and therefore extended ranges for practical implementations.

Analog backscatter enables sensing and communication while consuming significantly lower power than digital backscatter. An analog backscatter tag maps sensor readings directly to backscatter transmissions avoiding power hungry blocks such as ADCs. The sensor value variations are backscattered atop a carrier as changes in frequency and amplitude. Frequency variations are commonly used in backscatter, to avoid the strong self-interference from the carrier. The range of the sensor output linearly maps to the range of base-band frequency variation. Hence a sensor with a wider output range requires a larger base-band frequency range to encode sensor data at a high resolution. This increases the tag oscillator's switching frequency and hence the tag's power consumption. We propose to use higher order harmonic frequencies which allows us to reduce the tag switching frequency and read sensor data even when the carrier masks the fundamental frequency due to reduced switching frequency. Our system design lowers the cost and power consumption of the analog backscatter system making it suitable for mobile-based sensing applications. We present experimental results demonstrating the viability of our approach and implement a complete system that includes a low-cost radio receiver. Using a carrier with 0 dBm power, we detect the 15th harmonic up to three meters resulting in 15 times more frequency resolution than the fundamental while reducing the tag oscillator's power consumption by more than 43%. The 7th harmonic is visible up to 18 meters. Increasing the carrier power enables the detection of additional harmonic frequencies.

Wireless communications are critical in the constantly changing environment of IoT and RFID technologies, where thousands of devices can be deployed across a wide range of scenarios. Whether connecting to cloud servers or local fog/edge devices, maintaining seamless communications is difficult, especially in demanding contexts like industrial warehouses or remote rural areas. Opportunistic networks, when combined with edge devices, provide a possible solution to this challenge. These networks enable IoT devices, particularly mobile devices, to redirect information as it passes via other devices until it reaches an edge node. Using different communication protocols, this paper investigates their effects on response times and total messages received for a opportunistic assisted RFID system. Specifically, this article compares two communications technologies (Bluetooth 5 and Wize) when used for building a novel Opportunistic Edge Computing (OEC) identification system based on low-cost Single-Board Computers (SBCs). For such a comparison, measurements have been performed for quantifying packet loss and latency. The tests consisted in two experiments under identical conditions and scenarios, with a node located roadside, transmitting identification information, and a node located inside a moving vehicle that was driven at varying vehicle speeds. The obtained results show for Bluetooth 5 average latencies ranging between 700 and 950 ms with packet losses between 7% and 27%, whereas for Wize the average delay as between 150 and 370 ms with packet losses between 20% and 52%.

One of the main limitations for the development and deployment of many Green Radio Frequency Identification (RFID) and Internet of Things (IoT) systems is the access to energy sources. In this aspect batteries are the main option to be used in energy constrained scenarios, but their use is limited to certain cases, either because of the constraints imposed by a reduced-form factor, their limited lifespan, or the characteristics of the environment itself (e.g. operating temperature, risk of burning, need for fast response, sudden voltage variations). In this regard, supercapacitors present an interesting alternative for the previously mentioned type of environment, although, due to their short-term capacity, they must be combined with an alternative energy supply mechanism. Energy harvesting mechanisms in conjunction with ultra-low-power electronics, supercapacitors and various methods to improve the efficiency of communications, have enabled the emergence of battery-less passive electronic devices such as sensors, actuators or transmitters. This paper analyzes the performance of an energy harvesting system based on vibrations for Green RFID and IoT applications in the field of maritime transport. The results show that the proposed system allows for charging half of a 1.2 F supercapacitor in about 72 minutes providing a stable current of around 210 uA and a power output of 0.38 mW.

In this paper, we show how wideband measurement of threshold sensitivity and backscatter curves from generic T-matched RAIN (passive UHF) RFID tags can be used for determining magnetic properties of the tagged items. The method is based on measuring all three tag resonances (two for sensitivity and one for backscatter), calculating from those the natural resonant frequency of the tag antenna loop portion and its frequency shift relative to free space, and then extracting effective magnetic permeability. The method is robust to the presence of non-magnetic materials. Possible applications include item sortation for reuse/recycling and smart package inspection.

Radio Frequency Identification (RFID) plays a crucial role in object identification in the rapidly changing world of the Internet of Things (IoT). Therefore, innovating a simple and adaptive solution to evaluate tag authenticity to combat counterfeit products is increasingly important. This study introduces a novel approach using the Dynamic Wavelet Fingerprint (DWFP) technique to produce fingerprint-like images for chipless RFID tags. These fingerprints are created by using tag's distinct electromagnetic (EM) response, which is produced through natural randomness added to the planar resonator configuration in the fabrication process. The unique fingerprints provide a simple and intuitive way to identify cloned tags. The research rigorously assesses the efficacy of these fingerprints in detecting cloned tags across noiseless and noisy environment. After analyzing twelve different mother wavelets and utilizing two slicing algorithms, this study presents optimal combinations that exhibit an increased diversity among cloned tags and resilience against noise. The findings highlight the DWFP technique as a robust solution for bolstering RFID tag security. This research offers new possibilities in image-based identification, demonstrating the potential of DWFP to transform the authentication of RFID tags and mitigate counterfeiting risks.

The quality (Q) factor of chipless RFID sensors is essential to improve their performance and reliability for various sensing applications. Previous research has relied on the reader's sensitivity and RCS improvement, making the system more complex and costly. Therefore, this research aims to optimise the detection performance of chipless RFID sensors by improving their Q factor by optimising the properties of the substrate and geometry of the resonator. The methodology involves analysing the theoretical background of the Q factor using a slot ring resonator (SRR) and different resonator geometries (e.g., a new Pi-shaped resonator) to evaluate its impact on the Q factor. The results show that only choosing the optimum substrate thickness can further improve the Q factor. Furthermore, we compared the resonance frequency and its variation over distance to determine the detectability. These findings demonstrate that high-Q resonators, like the Pi-shaped resonator, can improve the accuracy and resolution of chipless RFID sensing applications.

In this paper we study and fabricate surface acoustic wave devices that combine magnetic field and temperature measurements and that integrate a radio-frequency identification functionality (RFID). The use of a reflective delay line design enables to control the amplitude of the RFID signal peaks while maximizing the sensitivity of the sensor. The latter is based on a double layer of magnetoelastic CoFeB film used as sensitive layer to the magnetic field and deposited on top of a ZnO-covered LiNbO3 Y-X substrate. This structure is used to generate a Love wave which enhances the sensitivity to the magnetic field. The achieved device demonstrates a high sensitivity to the magnetic field, a temperature compensation and reflected signal levels of -20 dB in a wired connection. The obtained sensitivity of 3630 ppm/mT (or 1.482 Hz/nT), is among the highest reported in the literature on magnetic SAW sensors.

In many RFID and wireless sensor applications, there is a need for integrated sensors that measure proximity or impedance. Sample applications include tamper-detection, object sorting, industrial controls, chemical sensing, and new types of non-invasive biomedical devices. However, the design of such sensors has been challenging due to the constraints of low-cost, low-power, and poor ADC resolution. In this context, we present the design of a low-cost non-contact impedance sensor circuit based on a JFET Clapp oscillator topology that uses minimal parts, and where the resonator coil is also used as the sensor antenna. In addition, we show how the loss and reactive components of the impedance can be independently derived from the amplitude and frequency as measured by an integrated frequency counter and diode detector. Measurement results are shown demonstrating the use of the sensor circuit with a commercial active RFID tag operating on a 3V coin cell battery and employing the IEEE 802.15.4 wireless protocol.

We demonstrate a new backscatter sensing modality that exploits the measurement of the channel between two backscatter tags. This channel is independent of the channel between the reader and each tag. A theoretical basis of the sensor modality for dipole tags in the near field is derived. A proof-of concept distance sensor, using commercial RFID tags, exhibits conformity to theory and demonstrates separation measurement with sub-centimetre accuracy.

In this paper, we describe our effort to extend the development of a standard framework for analog computing through further developing and integrating an existing high level synthesis (HLS) tool for analog system design. These Python and Scilab based tools allow designers to design and implement reconfigurable systems on field-programmable analog arrays (FPAA). In doing this, we can provide a way to have the same ease of development that digital integrated circuits (ICs) have with the field-programmable gate-array (FPGA). We describe the importance of analog computing, the state of the old tool flow, our contributions to upgrading the tool flow, and our demonstration of the working tools.

This study delves into the evolution of battery-less Radio-Frequency Identification (RFID) sensor tags, a technology that uses wireless communication for object, person, or animal identification and tracking. Recognized for their cost effectiveness, extended useful life and sustainability, these RFID tags are the focus due to their increasing significance. The main goal is to uncover trends and advances in batteryless RFID sensor systems, offering insights into their current status and future trajectories. The comprehensive review covers energy harvesting technologies, prevalent energy sources, participating countries, operational bands, and reading distances. The results indicate a predominant focus on the development of RFID devices without specific applications, with a notable emphasis on health and wellness applications. This study contributes valuable information on the dynamic landscape of battery-less RFID sensor technologies, fostering potential innovations in various sectors.

Sensing motion in a non-contact manner finds its application in numerous scenarios. It can be used for occupancy detection, to track vital signs, or to infer gestures. Radio frequency-based systems are often used to support these scenarios. Nonetheless, they are typically power-consuming and require sophisticated hardware and complex algorithms. In this paper, we present our work to design a low-power sensor that enables tracking of motions such as a person's breathing while consuming under 100 microwatts of power and at voltages as low as 70 millivolts. This enables our sensor to operate on energy harvested from photodiodes without using typical harvesters, which fail to operate well under low voltage conditions. The sensor is enabled through the unique properties of tunnel diodes, which we use to design a radio frequency oscillator that shows remarkable sensitivity to small changes in the environment. This is due to the coupling of electric, magnetic, and radio signals impacting the resonant property of the oscillator. The sensor is composed of a few components. It causes a change in the oscillator's frequency, simplifying the receiver design, as it does not have to extract reflections from stronger signals. We demonstrate the applicability of the sensor to track breathing.