In this study, we describe the realization of a time-of-flight scanning LiDAR (Light Detection and Ranging) prototype, that leverages mirrors as micro-electromechanical systems (MEMS) for agile beam steering in a compact size, and a field-programmable gate array (FPGA)-based processing unit for real-time 3D image reconstruction. The proposed 3D LiDAR system is designed to operate within a range of up to 1 meter with a spatial resolution of 400 × 300 pixels at a frame rate of 30 Hz. The LiDAR prototype architecture consists of 3 main parts: an optomechanical system, a digital processing unit (FPGA-based), an analog front-end. Processed 3D depth maps are rendered in real time via a high-definition multimedia interface (HDMI), providing immediate visual feedback. The full system was deeply characterized and tested. The integration of MEMS mirrors, an FPGA-based time-to-digital converter, and an optimized analog front-end resulted in a highly efficient, compact, and real-time depth sensing platform, ready for a final engineering step. The results obtained represent a feasibility study for a potential commercial product, that is low-cost and small-size, with different consumer applications.

Ultrasound techniques are widely used for monitoring chemical reactions and characterizing liquids. While the speed of sound in pure fatty acid esters (methyl and ethyl) is reasonably well established, the influence of molar ratio and alcohol type on the speed of sound in biodiesel across different frequencies remains unexplored. This study investigates the ultrasonic characterization of soybean biodiesel produced using different alcohols and molar ratios at frequencies of 1 MHz, 5 MHz, 7.5 MHz, and 10 MHz. The speed of sound in biodiesel samples was measured using the pulse–echo technique, with the expanded uncertainty determined at a 95 % confidence level. The results show that biodiesel samples produced with different alcohols at the same molar ratio exhibit distinct speed of sound values. Additionally, biodiesel synthesized at a 6:1 molar ratio demonstrated the lowest speed of sound. The findings confirm that ultrasound effectively differentiates biodiesel samples based on speed-of-sound measurements. This study highlights ultrasound as a promising technique for identifying biodiesel production pathways, offering a non-invasive and efficient analytical tool for quality assessment.

In the last two decades, the interest in digital image correlation (DIC) has grown steadily in various industrial and scientific fields, thanks to its contactless nature, capability to provide full field measurements, and ease of implementation. The possibility to carry out measurements in the presence of significant relative motion between the camera and the target has been thoroughly investigated. In dynamic conditions, the main additional source of uncertainty is represented by the motion blur effect, which is experienced whenever the relative displacement between the camera and the target during the exposure time is not negligible. Motion blur is a source of uncertainty, since it decreases the contrast in the image and the definition of the speckles in the acquired pattern. In this work, a complete procedure for motion blur estimation and compensation is considered. It was found that the uncertainty in the estimation of the blur intensity and orientation plays a crucial role in motion blur compensation. In this work, we propose a technique for the optimization of the blur estimation and compensation phases based on fitting the motion optical transfer function to a motion model. Compensation with a Wiener filter is then performed, studying different approaches to image noise estimation. Results show that the optimized procedure has a positive effect on DIC performances, being able to reduce the effect of motion blur on uncertainty, in particular for motion blur levels larger than about 1–2 px. The entire work has been validated by considering the procedure performances on DIC analysis performed on different kinds of speckle image with various amounts of motion blur applied.

Networked measurements are essential for the design and implementation of cooperative cyber-physical systems in the Industry 4.0/5.0 era. Indeed, the need for accurate models of real-time communication systems and, especially, of their latency is paramount for enabling technologies such as advanced manufacturing solutions, simulation and industrial internet. This paper presents a novel approach to measuring latency in wireless communication networks, focusing on the metrological characterization of individual subsystem contributions. By leveraging Time-Sensitive Networking (TSN) for synchronization, and employing cost-effective hardware solutions, we aim to provide a structured assessment of the measurement system’s capability to isolate and quantify latency contributions of individual communication modules, from the protocol stack to the Wireless Network Interface Controller (WNIC). The proposed approach is practical, flexible, and adaptable to various environments and deployment scenarios, representing a significant advancement in latency measurement techniques for modern network environments.

To address the new metrological challenges brought about by the digital revolution, a series of projects has recently been developed worldwide with the primary aim of promoting a new infrastructure for digital legal metrology. These projects include the use of cloud technologies to support conformity assessment processes, the development of infrastructure for digital calibration certificates, research on the comparability of real and virtual measurements, and the development of assessment methods for machine learning and artificial intelligence. The objective of the present paper is to present Pandora IRTech, a calibration and management software that utilises concepts and technologies from the Fourth Industrial Revolution. The software was built from a conceptual model based on state-of-the-art studies, process mapping, and risk assessment, identifying optimised structures and functionalities for its development. Finally, the applications created to optimise the calibration process and laboratory management in the current context of the digital revolution in metrology are presented and discussed.

This study focuses on the uncertainty analysis of pressure transducers, which are widely used in industrial applications. Pressure transducers convert mechanical pressure into electrical signals for measurement and monitoring across diverse sectors, like aerospace, automotive, and medical fields. The paper proposes a novel method for performing calibration uncertainty analysis through relativization, allowing the normalization of uncertainty contributions to various measurement parameters. By applying this approach, the study offers a standardized method to understand and quantify the impact of different sources of error on the overall measurement uncertainty. Furthermore, the techniques discussed in the study are applicable not only to pressure sensors but also to other measurement systems with multiple output units, contributing to the accuracy and reliability of measurement processes across various industries.

Integrating III-V solar cells with silicon (Si) shows great promise for advancing commercial solar cell technology. Various methods exist to combine III-V and silicon, each presenting unique obstacles. Our study focuses on different III-V solar cell configurations to enhance their compatibility with silicon cells. Using the SCAPS software, we conducted simulations to design an ideal III-V device that closely aligns with commercially available Si solar cells. By optimizing the base layer's thickness and doping level during the simulations, we achieved an impressive efficiency of 25.0 %.

This work presents a novel result in signal processing theory, addressing the statistical properties of least squares estimation when fitting sinusoidal models to noise-corrupted data—a fundamental operation in numerous signal processing applications. We rigorously demonstrate the previously unrecognized estimation bias in the root mean square (RMS) of residuals when processing signals with additive Gaussian white noise, even when the sinusoidal frequency is known. Our theoretical framework derives a closed-form expression for this bias. The analytical derivations are validated through comprehensive Monte Carlo simulations. This work contributes to current trends in robust signal parameter estimation, uncertainty quantification, and performance analysis of signal processing algorithms under non-ideal conditions—essential considerations for applications in communications, radar, sonar, audio, biomedical signal processing, and measurement.

The search for clean and sustainable energy sources has increased dramatically in recent years. As a result, research into Energy Harvesting (EH) technology has become increasingly important. EH allows powering low-consumption electronic devices by converting types of energy that are commonly neglected into electrical energy. In this scenario, piezoelectric materials stand out due to their property of converting kinetic energy into electrical energy. Therefore, this article aims to focus on the electrical characterization of a Polyvinylidene Fluoride (PVDF) piezoelectric transducer and a computer modelling of its behavior using the LTspice® software, as well as its coupling to an EH power management chip (LTC3588-1), as the initial phase of a research project aimed at developing a piezoelectric energy harvester (PEH).

This work aimed to present the production of a Certified Reference Material (CRM) of methamphetamine hydrochloride, as an important tool to ensure the quality of forensic results. Methamphetamine is a synthetic drug derived from amphetamine, which potentially stimulates the central nervous system, and its prolonged use can cause excessive anxiety, euphoria, bipolar disorder, and psychosis, among other health damages. To produce this batch of CRM, homogeneity and transport stability studies were carried out by High-Performance Liquid Chromatography with Photodiode Array Detection (HPLC-PDA) using the results of chromatographic area corrected by the mass fraction of the sample in the analyzed solution. Evaluation of stability under storage conditions and characterization of the material were performed by 1H qNMR, a ratio primary measurement procedure. The CRM showed neither considerable heterogeneity nor a tendency to instability under transport conditions (temperature of 50 °C up to 21 days) and storage conditions (20–25 °C). The certified purity value of methamphetamine hydrochloride was (999 ± 12) mg/g, equivalent to a mass fraction of (99.9 ± 1.2) g / (100 g), (k = 2).