Mappatura dell'impervious e consumo di suolo tramite analisi di change detection in telerilevamento

Il telerilevamento rappresenta un efficace strumento per il monitoraggio dell’ambiente e del territorio, grazie alla disponibilità di sensori che riprendono con cadenza temporale fissa porzioni della superficie terrestre. Le immagini multi/iperspettrali acquisite sono in grado di fornire informazioni per differenti campi di applicazione. In questo studio è stato affrontato il tema del consumo di suolo che rappresenta un’importante sfida per una corretta gestione del territorio, poiché direttamente connesso con i fenomeni del runoff urbano, della frammentazione ecosistemica e con la sottrazione di importanti territori agricoli. Ancora non esiste una definizione unica, ed anche una metodologia di misura, del consumo di suolo; in questo studio è stato definito come tale quello che provoca impermeabilizzazione del terreno. L’area scelta è quella della Provincia di Bologna che si estende per 3.702 km2 ed è caratterizzata a nord dalla Pianura Padana e a sud dalla catena appenninica; secondo i dati forniti dall’ISTAT, nel periodo 2001-2011 è stata la quarta provincia in Italia con più consumo di suolo. Tramite classificazione pixel-based è stata fatta una mappatura del fenomeno per cinque immagini Landsat. Anche se a media risoluzione, e quindi non in grado di mappare tutti i dettagli, esse sono particolarmente idonee per aree estese come quella scelta ed inoltre garantiscono una più ampia copertura temporale. Il periodo considerato va dal 1987 al 2013 e, tramite procedure di change detection applicate alle mappe prodotte, si è cercato di quantificare il fenomeno, confrontarlo con i dati esistenti e analizzare la sua distribuzione spaziale.

Design and characterization of Electrochemical Sensors for Organic Bioelectronics

This Ph.D. Thesis concerns the design and characterisation of functional electrochemical interfaces in organic electronic devices for bioelectronic applications. The Thesis is structured as follows: Chapter I – Technological context that has inspired the research, introduction to Organic Bioelectronics and literature review concerning Organic Electrochemical Transistors (OECTs) for sensing applications. Chapter II – Working principle of an all-polymeric OECT and operando microscopic characterization using scanning electrochemical techniques. Chapter III – Dopamine detection with all-polymeric OECT sensors. Development of a potentiodynamic approach to address selectivity issues in the presence of interfering species and design of a needle-type, sub-micrometric OECT sensor for spatially resolved detection of biological Dopamine concentrations. Chapter IV – Development of an OECT pH sensor. Characterization of the electrochemical transducer and functionalization of the OECT gate electrode with the sensing material. Potentiodynamic and potentiostatic operation modalities are explored and the sensing performances are assessed in both cases. The final device is realized on a flexible substrate and tested in Artificial Sweat. Chapter V – Study of two-terminal, electrochemically gated sensors inspired by the OECT configuration. Design and characterization of novel functional materials showing a potentiometric transduction of the chemical signal that can be exploited in the realization of electrochemical sensors with simplified geometry for wearable applications. Chapter VI – Conclusion.

Monitoring and Prediction of Thermal Emergencies in High Performance Computing Systems

Modern scientific discoveries are driven by an unsatisfiable demand for computational resources. High-Performance Computing (HPC) systems are an aggregation of computing power to deliver considerably higher performance than one typical desktop computer can provide, to solve large problems in science, engineering, or business. An HPC room in the datacenter is a complex controlled environment that hosts thousands of computing nodes that consume electrical power in the range of megawatts, which gets completely transformed into heat. Although a datacenter contains sophisticated cooling systems, our studies indicate quantitative evidence of thermal bottlenecks in real-life production workload, showing the presence of significant spatial and temporal thermal and power heterogeneity. Therefore minor thermal issues/anomalies can potentially start a chain of events that leads to an unbalance between the amount of heat generated by the computing nodes and the heat removed by the cooling system originating thermal hazards. Although thermal anomalies are rare events, anomaly detection/prediction in time is vital to avoid IT and facility equipment damage and outage of the datacenter, with severe societal and business losses. For this reason, automated approaches to detect thermal anomalies in datacenters have considerable potential. This thesis analyzed and characterized the power and thermal characteristics of a Tier0 datacenter (CINECA) during production and under abnormal thermal conditions. Then, a Deep Learning (DL)-powered thermal hazard prediction framework is proposed. The proposed models are validated against real thermal hazard events reported for the studied HPC cluster while in production. This thesis is the first empirical study of thermal anomaly detection and prediction techniques of a real large-scale HPC system to the best of my knowledge. For this thesis, I used a large-scale dataset, monitoring data of tens of thousands of sensors for around 24 months with a data collection rate of around 20 seconds.

Structural health monitoring of storage tanks

In this thesis, Ph.D candidate presents a compact sensor node (SN) designed for long-term and real-time acoustic emission (AE) monitoring of above ground storage tanks (ASTs). Each SN exploits up to three inexpensive low-frequency sensors based on piezoelectric diaphragms for effective leakage detection, and it is capable by means of built-in Digital Signal Processing functionalities to process the acquired time waveforms extracting the AE features usually required by testing protocols. Alternatively, capability to plug three high frequency AE sensors to a SN for corrosion simulated phenomena detection is envisaged and demonstrated. Another innovative aspect that the Ph.D candidate presents in this work is an alternative mathematical model of corrosion location on the bottom of the AST. This approach implies considering the three-dimensional localization model versus the two-dimensional commonly used according to the literature. This approach is aimed at significant optimization in the number of sensors in relation to the standard approach for solving localization problems as well as to allow filtering the false AE events related to the condensate droplets from AST ceiling. The technological implementation of this concept required the solution of a number of technical problems, such as the precise time of arrival (ToA) signal estimation, vertical localization of the AE source and multilaration solution that were discussed in detail in this work. To validate the developed prototype, several experimental campaigns were organized that included the simulation of target phenomena both in laboratory conditions and on a real water storage tank. The presented test results demonstrate the successful application of the developed AE system both for simulated leaks and for corrosion processes on the tank bottom. Mathematical and technological algorithms for localization and characterization of AE signals implemented during the development of the prototype are also confirmed by the test results.

Metrological characterization of sensors and instrumentation for distribution grid monitoring and electrical asset diagnostics

The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.

Solid state micro and nanopore sensors for single entity detection

A general description of the work presented in this thesis can be divided into three areas of interest: micropore fabrication, nanopore modification, and their applications. The first part of the thesis is related to the novel, reliable, cost-effective, potable, mass-productive, robust, and ease of use micropore flowcell that works based on the RPS technique. Based on our first goal, which was finding an alternate materials and processes that would shorten production times while lowering costs and improving signal quality, the polyimide film was used as a substrate to create precise pores by femtosecond laser, and the resulting current blockades of different sizes of the nanoparticles were recorded. Based on the results, the device can detecting nano-sized particles by changing the current level. The experimental and theoretical investigation, scanning electron microscopy, and focus ion beam were performed to explain the micropore's performance. The second goal was design and fabrication of a leak-free, easy-to-assemble, and portable polymethyl methacrylate flowcell for nanopore experiments. Here, ion current rectification was studied in our nanodevice. We showed a self-assembly-based, controllable, and monitorable in situ Poly(l-lysine)- g-poly(ethylene glycol) coating method under voltage-driven electrolyte flow and electrostatic interaction between nanopore walls and PLL backbones. Using designed nanopore flowcell and in situ monolayer PLL-g-PEG functionalized 20±4 nm SiN nanopores, we observed non-sticky α-1 anti-trypsin protein translocation. additionally, we could show the enhancement of translocation events through this non-sticky nanopore, and also, estimate the volume of the translocated protein. In this study, by comparing the AAT protein translocation results from functionalized and non-functionalized nanopore we demonstrated the 105 times dwell time reduction (31-0.59ms), 25% amplitude enhancement (0.24-0.3 nA), and 15 times event’s number increase (1-15events/s) after functionalization in 1×PBS at physiological pH. Also, the AAT protein volume was measured, close to the calculated AAT protein hydrodynamic volume and previous reports.

Sensor networks optimization and software development for Structural Health Monitoring based on ultrasonic guided waves

The Structural Health Monitoring (SHM) research area is increasingly investigated due to its high potential in reducing the maintenance costs and in ensuring the systems safety in several industrial application fields. A growing demand of new SHM systems, permanently embedded into the structures, for savings in weight and cabling, comes from the aeronautical and aerospace application fields. As consequence, the embedded electronic devices are to be wirelessly connected and battery powered. As result, a low power consumption is requested. At the same time, high performance in defects or impacts detection and localization are to be ensured to assess the structural integrity. To achieve these goals, the design paradigms can be changed together with the associate signal processing. The present thesis proposes design strategies and unconventional solutions, suitable both for real-time monitoring and periodic inspections, relying on piezo-transducers and Ultrasonic Guided Waves. In the first context, arrays of closely located sensors were designed, according to appropriate optimality criteria, by exploiting sensors re-shaping and optimal positioning, to achieve improved damages/impacts localisation performance in noisy environments. An additional sensor re-shaping procedure was developed to tackle another well-known issue which arises in realistic scenario, namely the reverberation. A novel sensor, able to filter undesired mechanical boundaries reflections, was validated via simulations based on the Green's functions formalism and FEM. In the active SHM context, a novel design methodology was used to develop a single transducer, called Spectrum-Scanning Acoustic Transducer, to actively inspect a structure. It can estimate the number of defects and their distances with an accuracy of 2[cm]. It can also estimate the damage angular coordinate with an equivalent mainlobe aperture of 8[deg], when a 24[cm] radial gap between two defects is ensured. A suitable signal processing was developed in order to limit the computational cost, allowing its use with embedded electronic devices.

Cross-sensors analysis of multispectral Earth observation data for environmental monitoring

Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.