This work proposes a novel system for location applications of RFID tags in UHF band. The system is based on a frequency-scanning leaky-wave antenna (LWA), commodity hardware and Angle-of-Arrival (AoA) estimation of the signal reflected from RFID tags, by using only RSSI (Received Signal Strength Indicator) data. The LWA is completely passive, manufactured in simple printed technology and directly connected to the RFID reader. The dispersive nature of the LWA combined with the selection of a proper high permittivity substrate allows the radiation of frequency steered directive beams. The system is based on four directive beams created by the two-port antenna and two RFID channels to estimate the AoA by amplitude-monopulse signal processing and angular pseudospectrum technique. Thus, our approach is efficient, simple and low-cost, since the use of expensive or complex hardware required for electronic phased-array steering/beam-switching is avoided and the required computational load is low. Several experiments have been performed in different scenarios, reporting a wide FoV of 130°, multi-tag detection and a RMSE of 8,1°.

Type 1 Diabetes Mellitus (DM1) is a condition of the metabolism typified by persistent hyperglycemia as a result of insufficient pancreatic insulin synthesis. This requires patients to be aware of their blood glucose level oscillations every day to deduce a pattern and anticipate future glycemia, and hence, decide the amount of insulin that must be exogenously injected to maintain glycemia within the target range. This approach often suffers from a relatively high imprecision, which can be dangerous. Nevertheless, current developments in Information and Communication Technologies (ICT) and innovative sensors for biological signals that might enable a continuous, complete assessment of the patient’s health provide a fresh viewpoint on treating DM1. With this, we observe that current biomonitoring devices and Continuous Glucose Monitoring (CGM) units can easily obtain data that allow us to know at all times the state of glycemia and other variables that influence its oscillations. A complete review has been made of the variables that influence glycemia in a T1DM patient and that can be measured by the above means. The communications systems necessary to transfer the information collected to a more powerful computational environment, which can adequately handle the amounts of data collected, have also been described. From this point, intelligent data analysis extracts knowledge from the data and allows predictions to be made in order to anticipate risk situations. With all of the above, it is necessary to build a holistic proposal that allows the complete and smart management of T1DM. This approach evaluates a potential shortage of such suggestions and the obstacles that future intelligent IoMT-DM1 management systems must surmount. Lastly, we provide an outline of a comprehensive IoMT-based proposal for DM1 management that aims to address the limits of prior studies while also using the disruptive technologies highlighted before.

Piezoelectric transducers are widely used for generating acoustic energy, and choosing the right radiating element is crucial for efficient energy conversion. In recent decades, numerous studies have been conducted to characterize ceramics based on their elastic, dielectric, and electromechanical properties, which have improved our understanding of their vibrational behavior and aided in the manufacturing of piezoelectric transducers for ultrasonic applications. However, most of these studies have focused on the characterization of ceramics and transducers using electrical impedance to obtain resonance and anti-resonance frequencies. Few studies have explored other important quantities such as acoustic sensitivity using the direct comparison method. In this work, we present a comprehensive study that covers the design, manufacturing, and experimental validation of a small-sized, easy-to-assemble piezoelectric acoustic sensor for low-frequency applications, using a soft ceramic PIC255 from PI Ceramic with a diameter of 10 $\mathrm{m}$$\mathrm{m}$ and a thickness of 5 $\mathrm{m}$$\mathrm{m}$. We present two methods, analytical and numerical, for sensor design, followed by experimental validation, allowing for a direct comparison of measurements with simulated results. This work provides a useful evaluation and characterization tool for future applications of ultrasonic measurement systems.

Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest.

In this work a new design concept in the field of microwave heating assisted chemical reactors is proposed focusing on two main innovations. The first one consists in combining the resonant cavity and the vessel in the same volume, improving the durability of the system by using a metallic material for the vessel. The second consists of integrating antennas as applicator ports for energy transmission from the magnetron into the cavity, instead of waveguides, allowing greater design flexibility in terms of cavity and system dimensions. In this work, a microwave reactor with four electromagnetic energy emitting antennas is optimized. This innovation is evaluated by means of a simulation model that solves the finite element method (FEM) using the commercial software COMSOL Multiphysics coupling radio frequency and heat transfer physics. Within this work, simulations have demonstrated the microwave heating process in the configured chemical reactor where the implementation of standard waveguides would not be possible due to the incompatible size required in the selected diameter dimension for 106 litres. Therefore, the results achieved lay the foundation for the construction of a microwave reactor intended to drive the industrial process of chemical recycling of polymers on a large industrial scale.