Monitoring and surveillance of buildings, especially in critical infrastructure is crucial to increase the lifetime of such structures. This is due to fact, that buildings from reinforced concrete, like bridges or road tunnels are prone to corrosion due to their exposition to the elements. For this task, wireless sensor nodes can be employed in structural health monitoring. In the last few years passive RFID sensors have been proposed to gather data from inside concrete structures. However, designing antennas which are operational inside concrete to transmit data from the sensor node to the outside world is extremely challenging, due to the fact that the performance of antennas is extremely depended on their surrounding material. In this work, the fully automatized design of an antenna for the UHF band in concrete with varying electrical properties is demonstrated. Using a novel multi objective optimization method, the antennas are operational over a wide range of dielectric properties of the surrounding materials. In contrast to conventional approaches, no air spacers or boxes are needed around the antenna. The antenna parameters have been carefully obtained during the curing and drying process, in an outdoor like environment with 65% relative humidity. After 157 days of drying, a reflection coefficient of -13 dB and an antenna gain of -8.4 dBi is achieved, at a water content of the concrete of 4.2% by mass.

This work introduces a low-cost open-source electrocardiography (ECG) simulator comprising both MATLAB software for signal generation and a dedicated circuit board for signal output via a commercial sound card. Synthetic, rate-dependent ECG simulation is based on third-order polynomials that are calculated in sections for the main waves and spikes, respectively. Besides the heart rate, the output profile is fully adjustable with respect to Einthoven lead signals I–III, the amplitudes of the individual ECG waves and spikes, as well as the constitution and intensity of common distortions. The underlying coefficients for the synthetic ECG profile are obtained experimentally by analysing recordings of 22 healthy individuals with heart rates in the range of 40–180 bpm. Eight of these recordings are selected to determine the coefficients for the polynomials (training set) while the remaining 14 serve as test set to evaluate their applicability and accuracy. Thereby, a mean correlation of 98.57% is found which is superior in comparison with a widely accepted rate-dependent ECG profile that is generated from square root and linear terms (correlation score: 91.46%). Although other use-cases are feasible, the focus of this work is the development of an ECG simulator for academic research and university education. Both the MATLAB source code and the circuit layout files are available in the online supplement stimulating further work on this topic.

The design and optimization of antennas for specific boundary conditions and parameters, such as size and frequency, for a given application, is a highly complex and time consuming process, which usually involves elaborate computer-aided software packages and/or methods. Additionally, trade-offs and co-dependencies have to be considered, when optimizing for a specific parameter, i.e., a high antenna gain goes usually hand-in-hand with a large antenna. Therefore, we implemented a method that involves the automated design and optimization of asymmetrical pixelated antennas using evolutionary algorithms, where arbitrary parameters can be optimized for chosen boundary conditions. In contrast to other approaches, shifted cross elements were employed as pixels to avoid point contact defects. We present results for antennas with an exemplary resonant frequency of 868 MHz and sizes of 3 × 3, 4 × 4 and 6 × 6 cm. The agreement between measurements and simulations for the antenna gain and reflection coefficient is excellent, with a maximum error of 1.15% for the single resonant frequency (relative error) and 1.35 dB for the antenna gain (mean absolute error).

The swift and automated design of antennas remains a challenging aspect in research due to the specific design needs for individual applications. Alterations in resonance frequency or boundary conditions necessitate time-consuming re-designs. Though the application of evolutionary optimization and generative methods in general to antenna design has seen success, it has been mostly restricted to two-dimensional structures. In this work, we present an approach for designing three-dimensional antennas using a genetic algorithm coupled with a region-growing algorithm - to ensure manufacturability - implemented in Matlab manufactured via laser powder bed fusion (LPBF). As a simulation tool for optimization CST is used. The antenna has been optimized in a completely automated manner and was produced using the metal 3D printing technology LPBF and aluminium based AlSi10Mg powder. The presented concept, which builds upon previous two-dimensional techniques, allows for significant flexibility in design, adapting to changing boundary conditions, and avoiding the geometric restrictions seen in prior methods. The optimized antenna has a size of 3.01 cm × 3.43 cm × 1.67 cm and was measured in an anechoic chamber. According to measurements a minimum reflection coefficient of -19.95 dB at 2.462 GHz and a bandwidth of 308.8MHz are observed. CST simulation results predict an efficiency of 98.91% and the maximum antenna gain is measured at 2.45 GHz to be 3.27 dBi. Simulations made with CST and Ansys HFSS and measurements are in excellent agreement with a deviation of the resonance frequency of only 0.13%, thus further establishing genetic algorithms as a highly viable option for the design of novel antenna structures.

In the context of the Internet of Things, billions of devices—especially sensors—will be linked together in the next few years. A core component of wireless passive sensor nodes is the rectifier, which has to provide the circuit with sufficient operating voltage. In these devices, the rectifier has to be as energy efficient as possible in order to guarantee an optimal operation. Therefore, a numerical optimization scheme is proposed in this paper, which is able to find a unique optimal solution for an integrated Complementary Metal-Oxide-Semiconductor (CMOS) rectifier circuit with Self-Vth-Cancellation (SVC). An exploration of the parameter space is carried out in order to generate a meaningful target function for enhancing the rectified power for a fixed communication distance. In this paper, a mean conversion efficiency is introduced, which is a more valid target function for optimization than the Voltage Conversion Efficiency (VCE) and the commonly used Power Conversion Efficiency (PCE) and is defined as the arithmetic mean between PCE and VCE. Various trade-offs between output voltage, PCE, VCE and MCE are shown, which provide valuable information for low power rectifier designs. With the proposed method, a rectifier in a low power 55 nm process from Globalfoundries (GF55LPe) is optimized and simulated at −30 dBm input power. A mean PCE of 63.33% and a mean VCE of 63.40% is achieved.

This article presents a detailed analysis of pixelated antennas employing shifted cross‐shaped elements optimised by evolutionary algorithms. Although, the size and number of the involved pixels, as well as the overall antenna size strongly influence performance of such antennas, detailed investigations on the interplay of geometrical considerations and their influence on parameters such as gain are missing from literature. Thus, the influence of various geometrical parameters on the performance of pixelated antennas for the first time, resulting in valuable design considerations is presented in this study. A maximum cross size could be found, for which an optimisation is viable. Based on this, a dataset consisting of 400 pixelated antennas was created, for different pixel‐ and antenna sizes and investigated certain parameters such as bandwidth and antenna gain. Most notably, a directly proportional dependence from the pixel‐on the antenna size for the optimisation of electrically large antennas was found. For small antennas, this dependency begins to deviate, leading to the fact that smaller pixels are needed to successfully optimise an antenna. Furthermore, the authors find that multi‐objective optimisation is a necessity to optimise matched antennas with a defined bandwidth and gain. The antenna gain shows a dependency on the cross size for electrically small antennas. From these results, design considerations for pixelated antennas can be derived. In addition to the extensive simulations, the dataset was verified in laboratory measurements.