In this paper, we present two novel dual-band bandpass filters based on surface plasmon polariton-like (SPP-like) propagation induced by structural dispersion of substrate integrated waveguide (SIW). Both filters are realized as a three-layer SIW where each layer represents asub-SIWstructure with intrinsic effective permittivity that depends on its width and filling dielectric material. The layers are designed to have effective permittivities of opposite signs in certain frequency ranges, which enables SPP-like propagation to occur at their interfaces. Since three layers can provide two distinct SPP-like propagations, the filters exhibit dual-band behaviour. A detailed theoretical and numerical analysis and numerical optimization have been used to design the filters, which were afterwards fabricated using standard printed circuit board technology. The independent choice of geometrical parameters ofsub-SIWsand/or the corresponding dielectric materials provide a great freedom to arbitrarily position the passbands in the spectrum, which is a significant advantage of the proposed filters. At the same time, they meet the requirements for low-cost low-profile configuration since they are realized as SIW structures, as well as for excellent in-band characteristics and selectivity which is confirmed by the measurement results.

This paper presents an autonomous robotic system, an unmanned ground vehicle (UGV), for in-field soil sampling and analysis of nitrates. Compared to standard methods of soil analysis it has several advantages: each sample is individually analyzed compared to average sample analysis in standard methods; each sample is georeferenced, providing a map for precision base fertilizing; the process is fully autonomous; samples are analyzed in real-time, approximately 30 min per sample; and lightweight for less soil compaction. The robotic system has several modules: commercial robotic platform, anchoring module, sampling module, sample preparation module, sample analysis module, and communication module. The system is augmented with an in-house developed cloud-based platform. This platform uses satellite images, and an artificial intelligence (AI) proprietary algorithm to divide the target field into representative zones for sampling, thus, reducing and optimizing the number and locations of the samples. Based on this, a task is created for the robot to automatically sample at those locations. The user is provided with an in-house developed smartphone app enabling overview and monitoring of the task, changing the positions, removing and adding of the sampling points. The results of the measurements are uploaded to the cloud for further analysis and the creation of prescription maps for variable rate base fertilization.

Due to the global water crisis there is a strong need for real-time water quality monitoring with high temporal and spatial resolution. This paper presents an economical multiparameter water quality monitoring system for continuous monitoring of fresh waters. It is based on a sensor node that integrates turbidity, temperature, and conductivity sensors, a miniature eighteen-channel spectrophotometer, and a sensor for the detection of thermotolerant coliforms, which is a major novelty of the system. Due to the influence of water impurities on the measurement of thermotolerant coliforms, a heuristic method has been developed to mitigate this effect. Moreover, the sensor is low power and with an integrated Long Range Wide Area Network module, it comprises a system that is wireless sensor network ready and can send data to a dedicated server. In addition, the system is submersible, capable of long-term field operation, and significantly cheaper in comparison to existing solutions. The purpose of the system is to give early warning of incidental pollution situations, thus enabling authorities to take action regarding further prevention of such occasions.

In this article, we propose a novel microfluidic microstrip electromagnetic band gap (EBG) sensor realized using cost-effective 3D printing technology. Microstrip sensor allows monitoring of the fluid properties flowing in the microchannel embedded between the microstrip line and ground plane. The sensor’s operating principle is based on the phase-shift method, which allows the characterization at a single operating frequency of 6 GHz. The defected electromagnetic band gap (EBG) structure is realized as a pattern in the microstrip ground plane to improve sensor sensitivity. The designed microfluidic channel is fabricated using a fused deposition modelling (FDM) 3D printing process without additional supporting layers, while the conductive layers are realized using sticky aluminium tape. The measurement results show that the change of permittivity of the fluid in the microfluidic channel from 1 to 80 results in the phase-shift difference of almost 90°. The potential application is demonstrated through the implementation of a proposed sensor for the detection of toluene concentration in toluene–methanol mixture where various concentrations of toluene were analysed.

This paper presents a very accurate sensor for the measurement of the moisture of undisturbed soil samples. The sensor relies on accurate estimation of the permittivity which is performed independently of the soil type, and a subsequent calibration. The sensor is designed as an upgrade of the conventional soil sampling equipment used in agriculture—the Kopecky cylinder. The detailed description of the device is given, and the method for determining soil moisture is explained in detail. Soil moisture of unknown test samples was measured with an absolute error below 0.0057 g/g, which is only 2.24% of the full scale output, illustrating the high accuracy of the sensor.