Optimal Excitation and Readout of Resonators Used as Wireless Passive Sensors.

Resonators are passive time-invariant components that do not produce a frequency shift. However, they respond to an excitation signal close to resonance with an oscillation at their natural frequencies with exponentially decreasing amplitudes. If resonators are connected to antennas, they form purely passive sensors that can be read remotely. In this work, we model the external excitation of a resonator with different excitation signals and its subsequent decay characteristics analytically as well as numerically. The analytical modeling explains the properties of the resonator during transient response and decay behavior. The analytical modeling clarifies how natural oscillations are generated in a linear time-invariant system, even if their spectrum was not included in the stimulation spectrum. In addition, it enables the readout signals to be optimized in terms of duration and bandwidth.

Automatic Life Detection Based on Efficient Features of Ground-Penetrating Rescue Radar Signals.

Good feature engineering is a prerequisite for accurate classification, especially in challenging scenarios such as detecting the breathing of living persons trapped under building rubble using bioradar. Unlike monitoring patients' breathing through the air, the measuring conditions of a rescue bioradar are very complex. The ultimate goal of search and rescue is to determine the presence of a living person, which requires extracting representative features that can distinguish measurements with the presence of a person and without. To address this challenge, we conducted a bioradar test scenario under laboratory conditions and decomposed the radar signal into different range intervals to derive multiple virtual scenes from the real one. We then extracted physical and statistical quantitative features that represent a measurement, aiming to find those features that are robust to the complexity of rescue-radar measuring conditions, including different rubble sites, breathing rates, signal strengths, and short-duration disturbances. To this end, we utilized two methods, Analysis of Variance (ANOVA), and Minimum Redundancy Maximum Relevance (MRMR), to analyze the significance of the extracted features. We then trained the classification model using a linear kernel support vector machine (SVM). As the main result of this work, we identified an optimal feature set of four features based on the feature ranking and the improvement in the classification accuracy of the SVM model. These four features are related to four different physical quantities and independent from different rubble sites.

Frequency Comb-Based Ground-Penetrating Bioradar: System Implementation and Signal Processing.

Radars can be used as sensors to detect the breathing of victims trapped under layers of building materials in catastrophes like earthquakes or gas explosions. In this contribution, we present the implementation of a novel frequency comb continuous wave (FCCW) bioradar module using a commercial software-defined radio (SDR). The FCCW radar transmits multiple equally spaced frequency components simultaneously. The data acquisition of the received combs is frequency domain-based. Hence, it does not require synchronization between the transmit and receive channels, as time domain-based broadband radars, such as ultra wideband (UWB) pulse radar and frequency-modulated CW (FMCW) radar, do. Since a frequency comb has an instantaneous wide bandwidth, the effective scan rate is much higher than that of a step frequency CW (SFCW) radar. This FCCW radar is particularly suitable for small motion detection. Using inverse fast Fourier transform (IFFT), we can decompose the received frequency comb into different ranges and remove ghost signals and interference of further range intervals. The frequency comb we use in this report has a bandwidth of only 60 MHz, resulting in a range resolution of up to 2.5 m, much larger than respiration-induced chest wall motions. However, we demonstrate that in the centimeter range, motions can be detected and evaluated by processing the received comb signals. We want to integrate the bioradar into an unmanned aircraft system for fast and safe search and rescue operations. As a trade-off between ground penetrability and the size and weight of the antenna and the radar module, we use 1.3 GHz as the center frequency. Field measurements show that the proposed FCCW bioradar can detect an alive person through different nonmetallic building materials.

Wireless Passive Sensor Technology through Electrically Conductive Media over an Acoustic Channel.

Hydrogen-based technologies provide a potential route to more climate-friendly mobility in the automotive and aviation industries. High-pressure tanks consisting of carbon-fiber-reinforced polymers (CFRPs) are exploited for the storage of compressed hydrogen and have to be monitored for safe and long-term operation. Since neither wired sensors nor wireless radio technology can be used inside these tanks, acoustic communication through the hull of the tank has been the subject of research in recent years. In this paper, we present for the first time a passive wireless sensor technology exploiting an ultrasonic communication channel through an electrically conductive transmission medium with an analog resonant sensor featuring a high quality factor. The instrumentation system comprised a readout unit outside and a passive sensor node inside the tank, coupled with geometrically opposing electromechanical transducers. The readout unit wirelessly excited a resonant sensor, whose temperature-dependent resonance frequency was extracted from the backscattered signal. This paper provides a description of the underlying passive sensor technology and characterizes the electric impedances and acoustic transmission as an electrical 2-Port to design a functional measurement setup. We demonstrated a wireless temperature measurement through a 10 mm CFRP plate in its full operable temperature range from -40 to 110 °C with a resolution of less than 1 mK.

Sensor Selection for Tidal Volume Determination via Linear Regression-Impact of Lasso versus Ridge Regression.

The measurement of respiratory volume based on upper body movements by means of a smart shirt is increasingly requested in medical applications. This research used upper body surface motions obtained by a motion capture system, and two regression methods to determine the optimal selection and placement of sensors on a smart shirt to recover respiratory parameters from benchmark spirometry values. The results of the two regression methods (Ridge regression and the least absolute shrinkage and selection operator (Lasso)) were compared. This work shows that the Lasso method offers advantages compared to the Ridge regression, as it provides sparse solutions and is more robust to outliers. However, both methods can be used in this application since they lead to a similar sensor subset with lower computational demand (from exponential effort for full exhaustive search down to the order of O (n2)). A smart shirt for respiratory volume estimation could replace spirometry in some cases and would allow for a more convenient measurement of respiratory parameters in home care or hospital settings.

Characterisation and Quantification of Upper Body Surface Motions for Tidal Volume Determination in Lung-Healthy Individuals.

Measurement of accurate tidal volumes based on respiration-induced surface movements of the upper body would be valuable in clinical and sports monitoring applications, but most current methods lack the precision, ease of use, or cost effectiveness required for wide-scale uptake. In this paper, the theoretical ability of different sensors, such as inertial measurement units, strain gauges, or circumference measurement devices to determine tidal volumes were investigated, scrutinised and evaluated. Sixteen subjects performed different breathing patterns of different tidal volumes, while using a motion capture system to record surface motions and a spirometer as a reference to obtain tidal volumes. Subsequently, the motion-capture data were used to determine upper-body circumferences, tilt angles, distance changes, movements and accelerations-such data could potentially be measured using optical encoders, inertial measurement units, or strain gauges. From these parameters, the measurement range and correlation with the volume signal of the spirometer were determined. The highest correlations were found between the spirometer volume and upper body circumferences; surface deflection was also well correlated, while accelerations carried minor respiratory information. The ranges of thorax motion parameters measurable with common sensors and the values and correlations to respiratory volume are presented. This article thus provides a novel tool for sensor selection for a smart shirt analysis of respiration.

Behavioral Modeling of DC/DC Converters in Self-Powered Sensor Systems with Modelica.

DC/DC converters are the essential component of power management in applications such as self-powered systems. Their simulation plays an important role in the configuration, analysis and design. A major drawback is the lack of behavioral models for DC/DC converters for long-term simulations (days or months). Available models are cycle-to-cycle-based due to the switch-mode nature of the converters and are therefore not applicable. In this work, we present a new behavioral model of a DC/DC power converter. The model is based on a thorough discussion of the model aspects that are relevant for self-powered systems, such as electrical representation and the causal connection if input and output. The model implementation is shown in the Modelica language and is available as an open-source library. The highlights of the model are a feedback controller for operation at the maximum power point (MPP), a loss-based efficiency function, and the start/stop behavior. The model's capabilities are demonstrated in a 24h-experiment to predict voltage levels and the conversion efficiency.

A Novel Electrically Small Ground-Penetrating Radar Patch Antenna with a Parasitic Ring for Respiration Detection.

An electrically small patch antenna with a low-cost high-permittivity ceramic substrate material for use in a ground-penetrating radar is proposed in this work. The antenna is based on a commercial ceramic 915 MHz patch antenna with a size of 25 × 25 × 4 mm3 and a weight of 12.9 g. The influences of the main geometric parameters on the antenna's electromagnetic characteristics were comprehensively studied. Three bandwidth improvement techniques were sequentially applied to optimize the antenna: tuning the key geometric parameters, adding cuts on the edges, and adding parasitic radiators. The designed antenna operates at around 1.3 GHz and has more than 40 MHz continuous -3 dB bandwidth. In comparison to the original antenna, the -3 and -6 dB fractional bandwidth is improved by 1.8 times and 4 times, respectively. Two antennas of the proposed design together with a customized radar were installed on an unmanned aerial vehicle (UAV) for a quick search for survivors after earthquakes or gas explosions without exposing the rescue staff to the uncertain dangers of moving on the debris.

Simultaneous Power Feedback and Maximum Efficiency Point Tracking for Miniaturized RF Wireless Power Transfer Systems.

Near-field interfaces with miniaturized coil systems and low output power levels, such as applied in biomedical sensor systems, can suffer from severe efficiency degradation due to dynamic impedance mismatches, reducing battery life of the power transmitter unit and requiring to increase the level of electromagnetic emission. Moreover, the stability of weakly-coupled power transfer systems is generally limited by transient changes in coil alignment and load power consumption. Hence, a central research question in the domain of wireless power transfer is how to realize an adaptive impedance matching system under the constraints of a simultaneous power feedback to increase the system's efficiency and stability, while maintaining circuit characteristics such as small size, low power consumption and fast reaction times. This paper presents a novel approach based on a two-stage control loop implemented in the primary-side reader unit, which uses a digital PI controller to maintain the rectifier output voltage for power feedback and an on-top perturb-and-observe controller configuring the setpoint of the voltage controller to maximize efficiency. The paper mathematically analyzes the AC and DC transfer characteristics of a resonant inductive link to design the reactive AC matching network, the digital voltage controller and ultimately the DC-domain impedance matching algorithm. It was found that static reactive L networks result in suitable efficiency levels for coils with sufficiently high quality factor even without adaptive tuning of operational frequency or reactive components. Furthermore, the regulated output voltage of the rectifier is a direct measure of the DC load impedance when using a regular DC/DC converter to supply the load circuits, so that this quantity can be tuned to maximize efficiency. A prototype implementation demonstrates the algorithms in a 40.68 MHz inductive link with load power levels from 10 to 100 mW and tuning time constants of 300 ms, while allowing for a simplified receiver with a footprint smaller than 200 mm2 and a self-consumption below 1 mW. Hence, the presented concepts enable adaptive impedance matching with favorable characteristics for low-energy sensor systems, i.e., minimized footprint, power level and reaction time.

Very High Bit Rate Near-Field Communication with Low-Interference Coils and Digital Single-Bit Sampling Transceivers for Biomedical Sensor Systems.

The evolution of microelectronics increased the information acquired by today's biomedical sensor systems to an extent where the capacity of low-power communication interfaces becomes one of the central bottlenecks. Hence, this paper mathematically analyzes and experimentally verifies novel coil and transceiver topologies for near-field communication interfaces, which simultaneously allow for high data transfer rates, low power consumption, and reduced interference to nearby wireless power transfer interfaces. Data coil design is focused on presenting two particular topologies which provide sufficient coupling between a reader and a wireless sensor system, but do not couple to an energy coil situated on the same substrate, severely reducing interference between wireless data and energy transfer interfaces. A novel transceiver design combines the approaches of a minimalistic analog front-end with a fully digital single-bit sampling demodulator, in which rectangular binary signals are processed by simple digital circuits instead of sinusoidal signals being conditioned by complex analog mixers and subsequent multi-bit analog-to-digital converters. The concepts are implemented using an analog interface in discrete circuit technology and a commercial low-power field-programmable gate array, yielding a transceiver which supports data rates of up to 6.78 MBit/s with an energy consumption of just 646 pJ/bit in transmitting mode and of 364 pJ/bit in receiving mode at a bit error rate of 2×10-7, being 10 times more energy efficient than any commercial NFC interface and fully implementable without any custom CMOS technology.

Acoustic Indoor Localization Augmentation by Self-Calibration and Machine Learning.

An acoustic transmitter can be located by having multiple static microphones. These microphones are synchronized and measure the time differences of arrival (TDoA). Usually, the positions of the microphones are assumed to be known in advance. However, in practice, this means they have to be manually measured, which is a cumbersome job and is prone to errors. In this paper, we present two novel approaches which do not require manual measurement of the receiver positions. The first method uses an inertial measurement unit (IMU), in addition to the acoustic transmitter, to estimate the positions of the receivers. By using an IMU as an additional source of information, the non-convex optimizers are less likely to fall into local minima. Consequently, the success rate is increased and measurements with large errors have less influence on the final estimation. The second method we present in this paper consists of using machine learning to learn the TDoA signatures of certain regions of the localization area. By doing this, the target can be located without knowing where the microphones are and whether the received signals are in line-of-sight or not. We use an artificial neural network and random forest classification for this purpose.

Load Measurement in Linear Guides for Machine Tools.

Process force determination in machine tools is an important topic for both optimization of manufacturing processes as well as predictive maintenance purposes. This work aims at providing a short overview of existing methods, motivating the integration of sensors into a linear guide, and then showing the results of an implemented new method for capturing the load on a rolling element linear guide by measuring the stresses resulting from the rolling element contact at the side of the runner block. The implementation of the approach is based on the piezoresistive diamond like carbon (DLC) coating DiaForce® provided by the Fraunhofer Institute for Surface Engineering and Thin Films (IST), Braunschweig, Germany. Good agreement of measurements with analytical and finite element method simulation results promises a stable modeling and load estimation process. Nevertheless, non-idealities due to high temperature dependency and cross-sensitivity to non rolling element contact related stresses could be shown, but also an efficient approach to diminish these effects is included.

Medlay: A Reconfigurable Micro-Power Management to Investigate Self-Powered Systems.

In self-powered microsystems, a power management is essential to extract, transfer and regulate power from energy harvesting sources to loads such as sensors. The challenge is to consider all of the different structures and components available and build the optimal power management on a microscale. The purpose of this paper is to streamline the design process by creating a novel reconfigurable testbed called Medlay. First, we propose a uniform interface for management functions e.g., power conversion, energy storing and power routing. This interface results in a clear layout because power and status pins are strictly separated, and inputs and outputs have fixed positions. Medlay is the ready-to-use and open-hardware platform based on the interface. It consists of a base board and small modules incorporating e.g., dc-dc converters, power switches and supercapacitors. Measurements confirm that Medlay represents a system on one circuit board, as parasitic effects of the interconnections are negligible. The versatility regarding different setups on the testbed is determined to over 250,000 combinations by layout graph grammar. Lastly, we underline the applicability by recreating three state-of-the-art systems with the testbed. In conclusion, Medlay facilitates building and testing power management in a very compact, clear and extensible fashion.

An Ultra-Low-Power RFID/NFC Frontend IC Using 0.18 µm CMOS Technology for Passive Tag Applications.

Battery-less passive sensor tags based on RFID or NFC technology have achieved much popularity in recent times. Passive tags are widely used for various applications like inventory control or in biotelemetry. In this paper, we present a new RFID/NFC frontend IC (integrated circuit) for 13.56 MHz passive tag applications. The design of the frontend IC is compatible with the standard ISO 15693/NFC 5. The paper discusses the analog design part in details with a brief overview of the digital interface and some of the critical measured parameters. A novel approach is adopted for the demodulator design, to demodulate the 10% ASK (amplitude shift keying) signal. The demodulator circuit consists of a comparator designed with a preset offset voltage. The comparator circuit design is discussed in detail. The power consumption of the bandgap reference circuit is used as the load for the envelope detection of the ASK modulated signal. The sub-threshold operation and low-supply-voltage are used extensively in the analog design—to keep the power consumption low. The IC was fabricated using 0.18 μ m CMOS technology in a die area of 1.5 mm × 1.5 mm and an effective area of 0.7 m m 2 . The minimum supply voltage desired is 1.2 V, for which the total power consumption is 107 μ W. The analog part of the design consumes only 36 μ W, which is low in comparison to other contemporary passive tags ICs. Eventually, a passive tag is developed using the frontend IC, a microcontroller, a temperature and a pressure sensor. A smart NFC device is used to readout the sensor data from the tag employing an Android-based application software. The measurement results demonstrate the full passive operational capability. The IC is suitable for low-power and low-cost industrial or biomedical battery-less sensor applications. A figure-of-merit (FOM) is proposed in this paper which is taken as a reference for comparison with other related state-of-the-art researches.

Wake-Up Receiver with Equal-Gain Antenna Diversity †.

Small scale fading signals resulting from multipath propagation can cause signal strength variations in the range of several dB. Resulting from the fluctuating signal strengths, the wake-up packet reception rate can decrease significantly. Using antenna diversity can greatly mitigate these effects. This article presents a novel wireless sensor node with wake-up receiver that uses an equal-gain diversity method with two antennas in the wake-up path. Summation of the two diversity branch signals is done after the passive demodulation of the incoming signals. As a result, the wireless sensor node requires almost no additional active parts that would increase power consumption. Furthermore, we demonstrate experimentally the improved wake-up robustness and reliability achieved by this diversity technique in a multipath environment.

Exploiting Concurrent Wake-Up Transmissions Using Beat Frequencies.

Wake-up receivers are the natural choice for wireless sensor networks because of their ultra-low power consumption and their ability to provide communications on demand. A downside of ultra-low power wake-up receivers is their low sensitivity caused by the passive demodulation of the carrier signal. In this article, we present a novel communication scheme by exploiting purposefully-interfering out-of-tune signals of two or more wireless sensor nodes, which produce the wake-up signal as the beat frequency of superposed carriers. Additionally, we introduce a communication algorithm and a flooding protocol based on this approach. Our experiments show that our approach increases the received signal strength up to 3 dB, improving communication robustness and reliability. Furthermore, we demonstrate the feasibility of our newly-developed protocols by means of an outdoor experiment and an indoor setup consisting of several nodes. The flooding algorithm achieves almost a 100% wake-up rate in less than 20 ms.

Decision-making behaviour during urban search and rescue: a case study of Germany.

The objective of assisting with tasks and decisions during incident response is to reduce the risks to victims and rescue personnel while increasing the efficiency of the rescue operation. Handling uncertain information during urban search and rescue (USAR) missions represents additional stress to the decision-maker. The aim of this study is to identify the decision-making behaviour of rescuers during USAR missions to pinpoint trapped or buried victims in debris in order to design assistance technologies and decision-support systems that meet their needs. In 2010, a survey was conducted among 10-15 per cent of all German rescue personnel specialised in search tasks. One of the major results of this survey is that a subjective assessment of the reliability of information available from heterogeneous sources influences the rescuers' actions and that there is no methodology for decision-making involving uncertain information. In addition, the study found that compliance with procedures does not require assistance.

Analysis of the acoustoelectric response of SAW gas sensors using a COM model.

Surface acoustic wave (SAW) gas sensors based on the acoustoelectric effect exhibit wide application prospects for in situ gas detection. However, establishing accurate models for calculating the scattering parameters of SAW gas sensors remains a challenge. Here, we present a coupling of modes (COM) model that includes the acoustoelectric effect and specifically explains the nonmonotonic variation in the center frequency with respect to the sensing film's sheet conductivity. Several sensing parameters of the gas sensors, including the center frequency, insertion loss, and phase, were experimentally compared for accuracy and practicality. Finally, the frequency of the phase extremum (FPE) shift was determined to vary monotonically, and the range of selectable test points was wide, making the FPE an appropriate response parameter for leveraging in SAW gas sensors. The simulation results of the COM model were highly consistent with the experimental results. Our study is proposed to provide theoretical guidance for the future development of gas SAW sensors.

Performance evaluation and comparative analysis of SubCarrier Modulation Wake-up Radio systems for energy-efficient wireless sensor networks.

Energy-efficient communication is one of the main concerns of wireless sensor networks nowadays. A commonly employed approach for achieving energy efficiency has been the use of duty-cycled operation of the radio, where the node's transceiver is turned off and on regularly, listening to the radio channel for possible incoming communication during its on-state. Nonetheless, such a paradigm performs poorly for scenarios of low or bursty traffic because of unnecessary activations of the radio transceiver. As an alternative technology, Wake-up Radio (WuR) systems present a promising energy-efficient network operation, where target devices are only activated in an on-demand fashion by means of a special radio signal and a WuR receiver. In this paper, we analyze a novel wake-up radio approach that integrates both data communication and wake-up functionalities into one platform, providing a reconfigurable radio operation. Through physical experiments, we characterize the delay, current consumption and overall operational range performance of this approach under different transmit power levels. We also present an actual single-hop WuR application scenario, as well as demonstrate the first true multi-hop capabilities of a WuR platform and simulate its performance in a multi-hop scenario. Finally, by thorough qualitative comparisons to the most relevant WuR proposals in the literature, we state that the proposed WuR system stands out as a strong candidate for any application requiring energy-efficient wireless sensor node communications.

Multi reflection of Lamb wave emission in an acoustic waveguide sensor.

Recently, an acoustic waveguide sensor based on multiple mode conversion of surface acoustic waves at the solid-liquid interfaces has been introduced for the concentration measurement of binary and ternary mixtures, liquid level sensing, investigation of spatial inhomogenities or bubble detection. In this contribution the sound wave propagation within this acoustic waveguide sensor is visualized by Schlieren imaging for continuous and burst operation the first time. In the acoustic waveguide the antisymmetrical zero order Lamb wave mode is excited by a single phase transducer of 1 MHz on thin glass plates of 1 mm thickness. By contact to the investigated liquid Lamb waves propagating on the first plate emit pressure waves into the adjacent liquid, which excites Lamb waves on the second plate, what again causes pressure waves traveling inside the liquid back to the first plate and so on. The Schlieren images prove this multi reflection within the acoustic waveguide, which confirms former considerations and calculations based on the receiver signal. With this knowledge the sensor concepts with the acoustic waveguide sensor can be interpreted in a better manner.