An Embedded In-Cabin Lightweight High-Performance 3D Gaze Estimation System

Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

O3b mPOWER Systems - Aero route modelling

The main goal of this internship is to develop a tool to perform a resource usage (and cost) estimation. There has been a major focus in the analysis of the gain levels and on the possibility of an outage. During the evaluation, it is shown that fast gain level adjustment has a major impact on link quality and resource consumption. On top of that, having a random outage during a flight is not a critical condition if even the simplest solution can be applied to overcome and compensate.

Multitemporal analysis of satellite imagery: implementation of a land evolution model in ALCS (ATSR LAND CLASSIFICATION SYSTEM)

In this report it was designed an innovative satellite-based monitoring approach applied on the Iraqi Marshlands to survey the extent and distribution of marshland re-flooding and assess the development of wetland vegetation cover. The study, conducted in collaboration with MEEO Srl , makes use of images collected from the sensor (A)ATSR onboard ESA ENVISAT Satellite to collect data at multi-temporal scales and an analysis was adopted to observe the evolution of marshland re-flooding. The methodology uses a multi-temporal pixel-based approach based on classification maps produced by the classification tool SOIL MAPPER ®. The catalogue of the classification maps is available as web service through the Service Support Environment Portal (SSE, supported by ESA). The inundation of the Iraqi marshlands, which has been continuous since April 2003, is characterized by a high degree of variability, ad-hoc interventions and uncertainty. Given the security constraints and vastness of the Iraqi marshlands, as well as cost-effectiveness considerations, satellite remote sensing was the only viable tool to observe the changes taking place on a continuous basis. The proposed system (ALCS – AATSR LAND CLASSIFICATION SYSTEM) avoids the direct use of the (A)ATSR images and foresees the application of LULCC evolution models directly to „stock‟ of classified maps. This approach is made possible by the availability of a 13 year classified image database, conceived and implemented in the CARD project (http://earth.esa.int/rtd/Projects/#CARD).The approach here presented evolves toward an innovative, efficient and fast method to exploit the potentiality of multi-temporal LULCC analysis of (A)ATSR images. The two main objectives of this work are both linked to a sort of assessment: the first is to assessing the ability of modeling with the web-application ALCS using image-based AATSR classified with SOIL MAPPER ® and the second is to evaluate the magnitude, the character and the extension of wetland rehabilitation.

Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Oxidative properties of the Iron - Thymine-1-acetic acid - Hydrogen peroxide catalytic system

The oxidation of alcohols and olefins is a pivotal reaction in organic synthesis. However, traditional oxidants are toxic and they often release a considerable amounts of by-products. Here, two IronIII-based systems are shown as oxidative catalyst, working in mild conditions with hydrogen peroxide as primary oxidant. An efficient catalytic system for the selective oxidation of several alcohols to their corresponding aldehydes and ketones was developed and characterized, [Fe(phen)2Cl2]NO3 (phen=1,10-Phenantroline). It was demonstrated that the adoption of a buffered aqueous solution is of crucial importance to ensure both considerable activity and selectivity.The Iron - Thymine-1-acetic acid in-situ complex was studied as catalyst in alcohol oxidations and C-H oxidative functionalization, involving hydrogen peroxide as primary oxidant in mild reaction conditions. The catalytic ability in alcohol oxidations was investigated by Density Functional Theory calculations, however the catalyst still has uncertain structure. The system shows satisfactory activity in alcohol oxidation and aliphatic rings functionalization. The Fe-THA system was studied in cyclohexene oxidation and oxidative halogenations. Halide salts such as NBu4X and NH4X were introduced in the catalytic system as halogens source to obtain cyclohexene derivatives such as halohydrins, important synthetic intermediates.The purpose of this dissertation is to contribute in testing new catalytic systems for alcohol oxidations and C-H functionalization. In particular, most of the efforts in this work focus on studying the Iron - Thymine-1-acetic acid (THA) systems as non-heme oxidative model, which present: •an iron metal centre(s) as a coordinative active site, •hydrogen peroxide as a primary oxidant, •THA as an eco-friendly, biocompatible, low cost coordinating ligand.

Night Vision Imaging System (NVIS) certification requirements analysis of an Airbus Helicopters H135

The safe operation of nighttime flight missions would be enhanced using Night Vision Imaging Systems (NVIS) equipment. This has been clear to the military since 1970s and to the civil helicopters since 1990s. In these last months, even Italian Emergency Medical Service (EMS) operators require Night Vision Goggles (NVG) devices that therefore amplify the ambient light. In order to fly with this technology, helicopters have to be NVIS-approved. The author have supported a company, to quantify the potentiality of undertaking the certification activity, through a feasibility study. Even before, NVG description and working principles have been done, then specifications analysis about the processes to make a helicopter NVIS-approved has been addressed. The noteworthy difference between military specifications and the civilian ones highlights non-irrevelant lacks in the latter. The activity of NVIS certification could be a good investment because the following targets have been achieved: Reductions of the certification cost, of the operating time and of the number of non-compliance.