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The automatic identification system (AIS) facilitates the monitoring of ship movements and provides essential input parameters for traffic safety. Previous studies have employed AIS data to detect behavioral anomalies and classify vessel types using supervised and unsupervised algorithms, including deep learning techniques. The approach proposed in this work focuses on the recognition of vessel types through the “Take One Class at a Time” (TOCAT) classification strategy. This approach pivots on a collection of adaptive models rather than a single intricate algorithm. Using radar data, these models are trained by taking into account aspects such as identifiers, position, velocity, and heading. However, it purposefully excludes positional data to counteract the inconsistencies stemming from route variations and irregular sampling frequencies. Using the given data, we achieved a mean accuracy of 83% on a 6-class classification task.

Landslides pose a significant risk to human life. The Twisting Theory (TWT) and Crown Clustering Algorithm (CCA) are innovative adaptive algorithms that can determine the shape of a landslide and predict its future evolution based on the movement of position sensors located in the affected area. In the first part of this study, the TWT and CCA will be thoroughly explained from a mathematical and theoretical perspective. In the second part, these algorithms will be applied to real-life cases, the Assisi landslide (1995–2008) and the Corvara landslide (2000–2008). A correlation of 0.9997 was attained between the model estimates and the expert’s posterior measurements at both examined sites. The results of these applications reveal that the TWT can accurately identify the overall shape of the landslides and predict their progression, while the CCA identifies complex cause-and-effect relationships among the sensors and represents them in a clear, weighted graph. To apply this model to a wider area and secure regions at risk of landslides, it is important to emphasize its operational feasibility as it only requires the installation of GNSS sensors in a predetermined grid in the target area.

Within a project co-funded by the Italian Ministry of Foreign Affairs, the final aim of which is to develop a WSN for smart monitoring of pesticides on agricultural land, the Italian and Serbian researchers have developed a hardware section of an electronic nose for pesticides. Since there are no specialized sensors which can smell the presence or absence of pesticides in the air, the electronic nose has been designed starting from an array of commercial gas sensors developed for other environmental applications. These sensors have a great advantage as they are COTS components. A measurement bench for testing the performance of the system has also been developed. Experimental tests have been conducted and the results have demonstrated the appropriateness of the idea. A test for calibration has been designed, as well, and it will be performed in the near future.

Starting from the Martian environment, we examine all the necessary requirements for a UAV and outline the architecture of a gyroplane optimized for scientific research and support for (future) Mars explorers, highlighting its advantages and criticalities. After a careful trade-off between different vehicles suitable for a typical mission, some parameters are established to optimize the size and performance. In the second part, the project of the Spider gyroplane and the methodology used to balance the longitudinal masses are presented; in the third part, the parameters of the aerodynamic forces acting on the aircraft are highlighted to be able to focus them during the fluid dynamics simulations.

The paper shows the steps for the preliminary studies of an AUV for shallow water: the first part illustrates the vehicle architecture and the philosophy that permeates the various design choices. In the second part illustrates an innovative method for increasing longitudinal stability based on Takagi-Sugeno (T-S) Fuzzy Inference System: it saves a lot of computational time and, by simplifying the calculation, it is also suitable for remarkably simple computers such as Arduino. in the third part is simulated the behavior of the AUV: thanks to the data taken from the previous hydrodynamic simulation, we can establish the behavior of its longitudinal stability and the computational savings due to the T-S method.

The paper shows the simulation of the behavior of a swarm of underwater drones (AUV) diffused in a closed section of the sea and inserted from a single starting point: Based on a few essential rules, we will see how their behavior evolves and how they manage to spread throughout the area assigned to them. In the first part of this work, after defining the design of the vehicle, we introduce our vision of the swarm, its problems, and its strengths. Later, we show how to spread a series of underwater drones with “diffused intelligence” (swarm) and its microscopic diffusion model. In the last part, we present the simulation that supports our approach to the swarm.

This paper is a section of several preliminary studies of the Underwater Drones Group of the Università degli Studi “Roma Tre„ Science Department: We describe the study philosophy, the theoretical technological considerations for sizing and the development of a technological demonstrator of a high accuracy buoyancy and depth control. We develop the main requirements and the boundary conditions that design the buoyancy system and develop the mathematical conditions that define the main parameters.

This paper focuses on the development of a new logistic approach based on reliability and maintenance assessment, with the final aim of establishing a more efficient interval for the maintenance activities for Unmanned Aerial Vehicles (UAV). In the first part, we develop an architectural philosophy to obtain a more detailed reliability evaluation; then, we study the intrinsic reliability at the design stage in order to avoid severe critical issues in the UAV. In the second part, we compare different maintenance philosophies for UAVs and develop the concepts of preventive and corrective maintenance that consider the system subjected (until real “hard failure”) to partial performance degradation (“soft failure”). Finally, by evaluation of the uncertainty through the confidence interval, we determine the new soft failure limits, taking into account the general knowledge of the systems and subsystems in order to guarantee the proper preventive maintenance interval.

The results of a comparison exercise of radiative transfer models (RTM) of various international research groups for Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) viewing geometry are presented. Besides the assessment of the agreement between the different models, a second focus of the comparison was the systematic investigation of the sensitivity of the MAX-DOAS technique under various viewing geometries and aerosol conditions. In contrast to previous comparison exercises, box-air-mass-factors (box-AMFs) for different atmospheric height layers were modelled, which describe the sensitivity of the measurements as a function of altitude. In addition, radiances were calculated allowing the identification of potential errors, which might be overlooked if only AMFs are compared. Accurate modelling of radiances is also a prerequisite for the correct interpretation of satellite observations, for which the received radiance can strongly vary across the large ground pixels, and might be also important for the retrieval of aerosol properties as a future application of MAX-DOAS. The comparison exercises included different wavelengths and atmospheric scenarios (with and without aerosols). The strong and systematic influence of aerosol scattering indicates that from MAX-DOAS observations also information on atmospheric aerosols can be retrieved. During the various iterations of the exercises, the results from all models showed a substantial convergence, and the final data sets agreed for most cases within about 5%. Larger deviations were found for cases with low atmospheric optical depth, for which the photon path lengths along the line of sight of the instrument can become very large. The differences occurred between models including full spherical geometry and those using only plane parallel approximation indicating that the correct treatment of the Earth's sphericity becomes indispensable. The modelled box-AMFs constitute an universal data base for the calculation of arbitrary (total) AMFs by simple convolution with a given trace gas concentration profile. Together with the modelled radiances and the specified settings for the various exercises, they can serve as test cases for future RTM developments.

We present the results of an intercomparison exercise between six different radiative transfer (RT) models carried out in the framework of QUILT, an EU funded project based on the exploitation of the Network for the Detection of Stratospheric Change (NDSC). RT modelling is an important step in the interpretation of Differential Optical Absorption Spectroscopy (DOAS) observations. It allows the conversion of slant column densities (SCDs) into vertical column densities (VCDs) using calculated air mass factors (AMFs). The originality of our study resides in comparing SCD simulations in multi-axis (MAX) geometry (trace gases: NO2 and HCHO) and in taking into account photochemical enhancement for calculating SCDs of rapidly photolysing species (BrO, NO2, and OClO) in zenith-sky geometry. Concerning the zenith-sky simulations, the different models agree generally well, especially below 90° SZA. At higher SZA, larger discrepancies are obtained with relative differences ranging between 2% and 14% in some cases. In MAX geometry, good agreement is found between the models with the calculated NO2 and HCHO SCDs differing by no more than 5% in the elevation and solar zenith angle (SZA) ranges investigated (5°–20° and 35°–85°, respectively). The impacts of aerosol scattering, ground albedo, and relative azimuth on MAX simulations have also been tested. Significant discrepancies appear for the aerosol effect, suggesting differences between models in the treatment of aerosol scattering. A better agreement is found in case of the ground albedo and relative azimuth effects. The complete set of initialization data and results have been made publicly available through the QUILT project web site (http://nadir.nilu.no/quilt/), enabling the testing of other RT codes designed for the calculation of SCDs/AMFs.

High tropospheric NO2 amounts are occasionally detected by space-borne spectrometers above cloudy scenes. For monitoring of near-ground air pollution such data are not directly applicable because clouds shield the highly polluted planetary boundary layer (PBL). We present a method based on trajectories which implicitly estimates the additional sub-cloud NO2 distribution in order to model concentrations at ground stations. The method is applied to a transboundary pollution transport episode which led to high NO2 vertical tropospheric column densities (VTCs) over middle Europe observed by the Global Ozone Monitoring Experiment (GOME) instrument above clouds on 17 February 2001. The case study shows that pollution originally residing near the ground in central Germany, the Ruhr area and adjacent parts of the Netherlands and Belgium has been advected to higher tropospheric levels by a passing weather front. Combining the above-cloud NO2 VTCs with trajectory information covering the GOME columns and including their sub-cloud part yields an estimate of the total NO2 distribution within the tropospheric columns. The highly polluted air masses are then traced by forward trajectories starting from the GOME columns to move further to the Alpine region and their impact there is assessed. Considering ground-based in-situ measurements in the Alpine region, we conclude that for this episode, at least 50% of the NO2 concentration recorded at the sites can be attributed to transboundary transport during the frontal passage. This study demonstrates the potential of using NO2 VTCs from GOME detected above clouds when combined with transport modelling.