Alessandro Bertacchini

Since LiDARs usually exploit near-infrared (NIR) radiation, we often do not even notice them. Nonetheless, they have become an almost constant presence that accompanies us most of the day. If, on the one hand, this has brought us advantages and simplifications, on the other, it will require ever greater attention to all aspects related to safety. Indeed, the LASER sources exploited by LiDARs can potentially pose risks to people. Since the received power decreases as the distance to the target increases, the farther away the objects to detect can be, the more powerful, and thus dangerous, the LASER source/s may need to be. In this scenario, 3D-scanning-LiDARs for automotive applications are probably among the most powerful LASER sources that any of us can come across in our daily lives. For our safety, compliance with the limits imposed by the safety standards must be guaranteed not only when the LiDAR, or the product including it, leaves the production line but throughout the entire operational life. Unfortunately, measuring the energy of each beam emitted by a 3D scanning LiDAR to verify its compliance with the limits imposed by the safety standards can be far from trivial. In this study, we exploit the peculiarities of 3D scanning LiDARs to propose a simplified method for testing the compliance of the emitted radiation with the limits for class 1 LASERs imposed by IEC 60825 standards. The method is primarily intended for automotive LiDARs but can be applied to most 3D scanning LiDARs.

The lack of general doctors and physicians represents the main problem for most of the modern national health systems. The high operating and maintenance costs of hospitals and clinics complete the critical picture. The development of new diagnostic tools can play a fundamental role in tackling these challenges. Recent studies have shown that electronic stethoscopes can raise the diagnostic suspicion of several pulmonary diseases, for instance interstitial lung diseases. The vibrating membrane, or diaphragm, is a fundamental component of the stethoscope that significantly affects its performance. Despite several theoretical and experimental studies are available about membrane vibration, the exact role of the diaphragm in a stethoscope for the acoustic coupling is still mostly unclear. In this paper we investigate the effect of the diaphragm on the sensibility and bandwidth of electronic stethoscopes. We setup a 1D numerical simulation of the system composed by the lung, human body, vibrating membrane and microphone. The parameters are devised from breathing mechanics and from the datasheets of a commercial diaphragm and microphone. The performance predicted by numerical simulations have been compared to experimental measurements on our prototype of electronic stethoscope. In particular, the predicted pressure at the input of the microphone is very close to that experimentally measured during outpatient visits at the University Hospital of Modena (Italy).

Dynamic on-resistance ( ${R}_{ \mathrm{\scriptscriptstyle ON}}{)}$ affects the stability of p-GaN power HEMTs. In Schottky-gate HEMTs, dynamic ${R}_{ \mathrm{\scriptscriptstyle ON}}$ is associated to either electron trapping at device surface or dynamic effects occurring in the buffer. However, in p-GaN HEMTs the floating p-GaN region can have an additional role on dynamic ${R}_{ \mathrm{\scriptscriptstyle ON}}$ , due to removal/injection of holes from/into the barrier with relatively long time constants, which can be erroneously interpreted as a reliability issue. In this letter, we present a model to explain the dynamic ${R}_{ \mathrm{\scriptscriptstyle ON}}$ due to surface-related effects in p-GaN power HEMTs. The model, called ‘hole virtual gate’, attributes the experimentally observed ${R}_{ \mathrm{\scriptscriptstyle ON}}$ instability due to negative/positive gate bias stress (NGS/PGS) to the charging/discharging of surface traps in the AlGaN barrier by the removal/injection of holes through the gate metal/p-GaN Schottky junction. We verify the validity of the model by means of calibrated numerical simulations, that correlate the activation energy ${E}_{\text {A}}~\approx ~0.4$ eV of both ${R}_{ \mathrm{\scriptscriptstyle ON}}$ increase/decrease during NGS/PGS to the thermal ionization energy of traps in the barrier.

The modern agriculture system based on open-field crops requires a lot of energy and resources in terms of soil, water, and chemicals. Vertical farming (VF) systems could be a viable alternative for some types of cultivation that are receiving interest thanks to their high modularity, optimized water and nutrients use, and LEDs employment as an energy-efficient light source. However, VF design and installation are expensive and require well-tailored optimization depending on the specific crop to increase its competitiveness. This work analyzed the effects of different combinations of NPK (nitrogen-phosphorus-potassium) slow-release fertilizers and LED-based light recipes on the growth of baby leaf lettuce (Lactuca sativa L.), taking advantage of the Design of Experiments (DoE) methodology. The type of slow-release fertilizer, its quantity measured as the number of aggregates from 0 to 6, and the type of light recipe were considered as input factors, and their possible influence on the growth of lettuce (in terms of morphological parameters) in a controlled indoor farming system was measured. Results suggest that using higher fertilizer inputs equal to six aggregates leads to an increase of average leaf area equal to 46% (from 13.00 cm² to 19.00 cm²), while the fresh weight of lettuce increases by 65% (from 1.79 g to 2.96 g). However, the height of plants also depends on the combination of the light recipes. In particular, the separate coupling of higher inputs of two fertilizers and light recipes leads to an increase in the height of lettuce equal to 33% (from 6.00 cm to 8.00 cm).

Indoor farms are a promising way to obtain vegetables in standard quantity and quality. As opposed to previous studies, this study attempts to calculate optimized LED light conditions for different growth stages (five-days time step) of basil (Ocimum basilicum) to enhance its indoor growth through a statistical approach. Design of Experiments (DoE) was used to plan a limited number of experiments (20) and to calculate quantitatively the effect of different light recipes on four responses: the number of plants, their height, the Leaf Area Index, and the amount of water used. Different proportions (from 25% to 77%) of Hyper Red (660 nm) and Deep Blue (451 nm), intensities in terms of LEDs–plant distance (60, 70 and 80 cm), and the addition of Warm White (3000 K) LEDs were considered as independent variables. The obtained models suggest that a light recipe tailored for every growth step in the plant’s life is beneficial. Appropriate LEDs must be carefully chosen at the beginning of growth, whereas distance becomes relevant at the end. This is confirmed by the results analysis carried out at the end of an additional growth test where the optimal light recipe extracted from the DoE’s results were used.

Condition Monitoring (CM) is an extremely critical application of the Internet of Things (IoT) within Industry 4.0 and Smart City scenarios, especially following the recent energy crisis. CM aims to monitor the status of a physical appliance over time and in real time in order to react promptly when anomalies are detected, as well as perform predictive maintenance tasks. Current deployments suffer from both interoperability and management issues within their engineering process at all phases – from their design to their deployment, to their management –, often requiring human intervention. Furthermore, the fragmentation of the IoT landscape and the heterogeneity of IoT solutions hinder a seamless onboarding process of legacy devices and systems. In this paper, we tackle these problems by first proposing an architecture for CM based on both abstraction layers and toolchains, i.e ., automated pipelines of engineering tools aimed at supporting the engineering process. In particular, we introduce four different toolchains, each of them dedicated to a well-defined task ( e.g ., energy monitoring). This orthogonal separation of concerns aims to simplify both the understanding of a complex ecosystem and the accomplishment of independent tasks. We then illustrate our implementation of a complete CM system that follows said architecture as a real Structural Health Monitoring (SHM) pilot of the Arrowhead Tools project, by describing in detail every single tool that we developed. We finally show how our pilot achieves the main objectives of the project: the reduction of engineering costs, the integration of legacy systems, and the interoperability with IoT frameworks.

This study follows a circular economy approach through the preliminary implementation of a coated porous inorganic material (PIM), studied as sustainable controlled release fertilizer, and its application for lettuce Lactuca sativa L. cultivar Chiara growth. The PIM was made of pumice scraps that partially replaced clay as a natural raw material, spent coffee grounds as a porous agent, bovine bone ash and potassium carbonate to provide phosphorus (P) and potassium (K) nutrients, respectively. A coating made with defatted black soldier fly prepupae biomass was used as a nitrogen (N) source. Most of the ingredients used were industrial residues, with the aim of valorizing the raw waste materials present locally. The suitability of PIMs as a fertilizer was investigated with an interdisciplinary approach, which included the first chemical and physical characterization of the material, the evaluation of its antibacterial properties and of its use in horticulture through lettuce growth tests. As tests were carried out indoors, a specific LED lighting device was used to grow the lettuce. The release of nutrients into the soil was estimated by measuring the main elements in the fertilizers before and after their use in the soil. The first results from this characterization study support PIMs’ suitability for agronomic applications. The use of the PIMs suggested average higher dry weight (49%), fresh weight (112%), and leaf area (48%), compared to those with the use of a standard fertilizer soil, without the release of any dangerous element for the plant in the soil. These results are a promising beginning for the development of further studies already in progress on sustainable controlled-release fertilizers.

This study aims to optimize artificial LEDs light conditions, for “Genovese” basil germination and growth in an indoor environment suitable for horticulture. Following a previous study on the synergic effect of LEDs light and a tailored fertilizer, in this study, the effect of white LED in combination with hyper red and deep blue, as well the plants–lights distance, was correlated to 14 growth and germination parameters, such as height, number of plants, etc. A design of experiments approach was implemented, aiming to derive mathematical models with predictive power, employing a restrained number of tests. Results demonstrated that for the germination phase, it is not possible to derive reliable mathematical models because almost the same results were found for all the experiments in terms of a fruitful germination. On the contrary, for the growth phase, the statistical analysis indicates that the distance among plants and lights is the most significant parameter. Nevertheless, correlations with LED light type emerged, indicating that white LEDs should be employed only to enhance specific growth parameters (e.g., to reduce water consumption). The tailored models derived in this study can be exploited to further enhance the desired property of interest in the growth of basil in horticulture.