Utilizzo delle bande dell’Infrarosso Termico in tecniche di remote sensing per applicazioni in ambito urbano

Il presente studio si concentra sulle diverse applicazioni del telerilevamento termico in ambito urbano. Vengono inizialmente descritti la radiazione infrarossa e le sue interazioni con l’atmosfera terrestre, le leggi principali che regolano lo scambio di calore per irraggiamento, le caratteristiche dei sensori e le diverse applicazioni di termografia. Successivamente sono trattati nel dettaglio gli aspetti caratteristici della termografia da piattaforma satellitare, finalizzata principalmente alla valutazione del fenomeno dell'Urban Heat Island; vengono descritti i sensori disponibili, le metodologie di correzione per gli effetti atmosferici, per la stima dell'emissività delle superfici e per il calcolo della temperatura superficiale dei pixels. Viene quindi illustrata la sperimentazione effettuata sull'area di Bologna mediante immagini multispettrali ASTER: i risultati mostrano come sull'area urbana sia riscontrabile la presenza dell'Isola di Calore Urbano, anche se la sua quantificazione risulta complessa. Si procede quindi alla descrizione di potenzialità e limiti della termografia aerea, dei suoi diversi utilizzi, delle modalità operative di rilievo e degli algoritmi utilizzati per il calcolo della temperatura superficiale delle coperture edilizie. Tramite l’analisi di alcune esperienze precedenti vengono trattati l’influenza dell’atmosfera, la modellazione dei suoi effetti sulla radianza rilevata, i diversi metodi per la stima dell’emissività. Viene quindi introdotto il progetto europeo Energycity, finalizzato alla creazione di un sistema GeoWeb di supporto spaziale alle decisioni per la riduzione di consumi energetici e produzione di gas serra su sette città dell'Europa Centrale. Vengono illustrate le modalità di rilievo e le attività di processing dei datasets digitali per la creazione di mappe di temperatura superficiale da implementare nel sistema SDSS. Viene infine descritta la sperimentazione effettuata sulle immagini termiche acquisite nel febbraio 2010 sulla città di Treviso, trasformate in un mosaico georiferito di temperatura radiometrica tramite correzioni geometriche e radiometriche; a seguito della correzione per l’emissività quest’ultimo verrà trasformato in un mosaico di temperatura superficiale.

Riabilitazione e valutazione di pazienti con deficit neurologici mediante l'utilizzo di realtà virtuale, feedback aumentati, sensori inerziali e tecnologie video a basso costo.

La neuroriabilitazione è un processo attraverso cui individui affetti da patologie neurologiche mirano al conseguimento di un recupero completo o alla realizzazione del loro potenziale ottimale benessere fisico, mentale e sociale. Elementi essenziali per una riabilitazione efficace sono: una valutazione clinica da parte di un team multidisciplinare, un programma riabilitativo mirato e la valutazione dei risultati conseguiti mediante misure scientifiche e clinicamente appropriate. Obiettivo principale di questa tesi è stato sviluppare metodi e strumenti quantitativi per il trattamento e la valutazione motoria di pazienti neurologici. I trattamenti riabilitativi convenzionali richiedono a pazienti neurologici l’esecuzione di esercizi ripetitivi, diminuendo la loro motivazione. La realtà virtuale e i feedback sono in grado di coinvolgerli nel trattamento, permettendo ripetibilità e standardizzazione dei protocolli. È stato sviluppato e valutato uno strumento basato su feedback aumentati per il controllo del tronco. Inoltre, la realtà virtuale permette l’individualizzare il trattamento in base alle esigenze del paziente. Un’applicazione virtuale per la riabilitazione del cammino è stata sviluppata e testata durante un training su pazienti di sclerosi multipla, valutandone fattibilità e accettazione e dimostrando l'efficacia del trattamento. La valutazione quantitativa delle capacità motorie dei pazienti viene effettuata utilizzando sistemi di motion capture. Essendo il loro uso nella pratica clinica limitato, una metodologia per valutare l’oscillazione delle braccia in soggetti parkinsoniani basata su sensori inerziali è stata proposta. Questi sono piccoli, accurati e flessibili ma accumulano errori durante lunghe misurazioni. È stato affrontato questo problema e i risultati suggeriscono che, se il sensore è sul piede e le accelerazioni sono integrate iniziando dalla fase di mid stance, l’errore e le sue conseguenze nella determinazione dei parametri spaziali sono contenuti. Infine, è stata presentata una validazione del Kinect per il tracking del cammino in ambiente virtuale. Risultati preliminari consentono di definire il campo di utilizzo del sensore in riabilitazione.

Movement Analysis by means of inertial sensors: from bench to bedside

in the everyday clinical practice. Having this in mind, the choice of a simple setup would not be enough because, even if the setup is quick and simple, the instrumental assessment would still be in addition to the daily routine. The will to overcome this limit has led to the idea of instrumenting already existing and widely used functional tests. In this way the sensor based assessment becomes an integral part of the clinical assessment. Reliable and validated signal processing methods have been successfully implemented in Personal Health Systems based on smartphone technology. At the end of this research project there is evidence that such solution can really and easily used in clinical practice in both supervised and unsupervised settings. Smartphone based solution, together or in place of dedicated wearable sensing units, can truly become a pervasive and low-cost means for providing suitable testing solutions for quantitative movement analysis with a clear clinical value, ultimately providing enhanced balance and mobility support to an aging population.

Electrochemical surface modification of Single walled carbon nanotubes and graphene-based electrodes for (bio)sensing applications

Sensors are devices that have shown widespread use, from the detection of gas molecules to the tracking of chemical signals in biological cells. Single walled carbon nanotube (SWCNT) and graphene based electrodes have demonstrated to be an excellent material for the development of electrochemical biosensors as they display remarkable electronic properties and the ability to act as individual nanoelectrodes, display an excellent low-dimensional charge carrier transport, and promote surface electrocatalysis. The present work aims at the preparation and investigation of electrochemically modified SWCNT and graphene-based electrodes for applications in the field of biosensors. We initially studied SWCNT films and focused on their topography and surface composition, electrical and optical properties. Parallel to SWCNTs, graphene films were investigated. Higher resistance values were obtained in comparison with nanotubes films. The electrochemical surface modification of both electrodes was investigated following two routes (i) the electrografting of aryl diazonium salts, and (ii) the electrophylic addition of 1, 3-benzodithiolylium tetrafluoroborate (BDYT). Both the qualitative and quantitative characteristics of the modified electrode surfaces were studied such as the degree of functionalization and their surface composition. The combination of Raman, X-ray photoelectron spectroscopy, atomic force microscopy, electrochemistry and other techniques, has demonstrated that selected precursors could be covalently anchored to the nanotubes and graphene-based electrode surfaces through novel carbon-carbon formation.

Sensori chimici basati su molecole e nanoparticelle

Con questo lavoro di tesi si è cercato da un lato di dare un contributo al settore dei sensori chimici, caratterizzando e sviluppando diversi sistemi che presentano promettenti proprietà per l’utilizzo nella realizzazione di sensori luminescenti, e dall’altro di studiare sistemi di nanoparticelle di oro per identificarne e caratterizzarne i processi che portano all’interazione con un’unità fluorescente di riferimento, il pirene. Quest’ultima parte della tesi, sviluppata nel capitolo 4, sebbene possa apparire “slegata” dall’ambito della sensoristica, in realtà non lo è in quanto il lavoro di ricerca svolto rappresenta una buona base di partenza per lo sviluppo di sistemi di nanoparticelle metalliche con un possibile impiego in campo biomedico e diagnostico. Tutte le specie studiate, seppur molto diverse tra loro, posseggono quindi buone caratteristiche di luminescenza ed interessanti capacità di riconoscimento, più o meno selettivo, di specie in soluzione o allo stato gassoso. L’approccio generale che è stato adottato comporta una iniziale caratterizzazione in soluzione ed una susseguente ottimizzazione del sistema mirata a passare al fissaggio su supporti solidi in vista di possibili applicazioni pratiche. A tal proposito, nel capitolo 3 è stato possibile ottenere un monostrato organico costituito da un recettore (un cavitando), dotato di una parte fluorescente le cui proprietà di luminescenza sono sensibili alla presenza di una funzione chimica che caratterizza una classe di analiti, gli alcoli. E’ interessante sottolineare come lo stesso sistema in soluzione si comporti in maniera sostanzialmente differente, mostrando una capacità di segnalare l’analita molto meno efficiente, anche in funzione di una diversa orientazione della parte fluorescente. All’interfaccia solido-gas invece, l’orientamento del fluoroforo gioca un ruolo chiave nel processo di riconoscimento, e ottimizzando ulteriormente il setup sperimentale e la composizione dello strato, sarà possibile arrivare a segnalare quantità di analita sempre più basse. Nel capitolo 5 invece, è stato preso in esame un sistema le cui potenzialità, per un utilizzo come sonda fluorescente nel campo delle superfici di silicio, sembra promettere molto bene. A tal proposito sono stati discussi anche i risultati del lavoro che ha fornito l’idea per la concezione di questo sistema che, a breve, verrà implementato a sua volta su superficie solida. In conclusione, le ricerche descritte in questa tesi hanno quindi contribuito allo sviluppo di nuovi chemosensori, cercando di migliorare sia le proprietà fotofisiche dell’unità attiva, sia quelle dell’unità recettrice, sia, infine, l’efficienza del processo di traduzione del segnale. I risultati ottenuti hanno inoltre permesso di realizzare alcuni prototipi di dispositivi sensoriali aventi caratteristiche molto promettenti e di ottenere informazioni utili per la progettazione di nuovi dispositivi (ora in fase di sviluppo nei laboratori di ricerca) sempre più efficienti, rispondendo in tal modo alle aspettative con cui questo lavoro di dottorato era stato intrapreso.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Supramolecular approaches to organized luminescent nanostructures for sensing, labeling and imaging applications

The common thread of this thesis is the will of investigating properties and behavior of assemblies. Groups of objects display peculiar properties, which can be very far from the simple sum of respective components’ properties. This is truer, the smaller is inter-objects distance, i.e. the higher is their density, and the smaller is the container size. “Confinement” is in fact a key concept in many topics explored and here reported. It can be conceived as a spatial limitation, that yet gives origin to unexpected processes and phenomena based on inter-objects communication. Such phenomena eventually result in “non-linear properties”, responsible for the low predictability of large assemblies. Chapter 1 provides two insights on surface chemistry, namely (i) on a supramolecular assembly based on orthogonal forces, and (ii) on selective and sensitive fluorescent sensing in thin polymeric film. In chapters 2 to 4 confinement of molecules plays a major role. Most of the work focuses on FRET within core-shell nanoparticles, investigated both through a simulation model and through experiments. Exciting results of great applicative interest are drawn, such as a method of tuning emission wavelength at constant excitation, and a way of overcoming self-quenching processes by setting up a competitive deactivation channel. We envisage applications of these materials as labels for multiplexing analysis, and in all fields of fluorescence imaging, where brightness coupled with biocompatibility and water solubility is required. Adducts of nanoparticles and molecular photoswitches are investigated in the context of superresolution techniques for fluorescence microscopy. In chapter 5 a method is proposed to prepare a library of functionalized Pluronic F127, which gives access to a twofold “smart” nanomaterial, namely both (i)luminescent and (ii)surface-functionalized SCSSNPs. Focus shifts in chapter 6 to confinement effects in an upper size scale. Moving from nanometers to micrometers, we investigate the interplay between microparticles flowing in microchannels where a constriction affects at very long ranges structure and dynamics of the colloidal paste.

Novel techniques for the remote sensing of photosynthetic processes

Remote sensing (RS) techniques have evolved into an important instrument to investigate forest function. New methods based on the remote detection of leaf biochemistry and photosynthesis are being developed and applied in pilot studies from airborne and satellite platforms (PRI, solar-induced fluorescence; N and chlorophyll content). Non-destructive monitoring methods, a direct application of RS studies, are also proving increasingly attractive for the determination of stress conditions or nutrient deficiencies not only in research but also in agronomy, horticulture and urban forestry (proximal RS). In this work I will focus on some novel techniques recently developed for the estimation of photochemistry and photosynthetic rates based (i) on the proximal measurement of steady-state chlorophyll fluorescence yield, or (ii) the remote sensing of changes in hyperspectral leaf reflectance, associated to xanthophyll de-epoxydation and energy partitioning, which is closely coupled to leaf photochemistry and photosynthesis. I will also present and describe a mathematical model of leaf steady-state fluorescence and photosynthesis recently developed in our group. Two different species were used in the experiments: Arbutus unedo, a schlerophyllous Mediterranean species, and Populus euroamericana, a broad leaf deciduous tree widely used in plantation forestry. Results show that ambient fluorescence could provide a useful tool for testing photosynthetic processes from a distance. These results confirm also the photosynthetic reflectance index (PRI) as an efficient remote sensing reflectance index estimating short-term changes in photochemical efficiency as well as long-term changes in leaf biochemistry. The study also demonstrated that RS techniques could provide a fast and reliable method to estimate photosynthetic pigment content and total nitrogen, beside assessing the state of photochemical process in our plants’ leaves in the field. This could have important practical applications for the management of plant cultivation systems, for the estimation of the nutrient requirements of our plants for optimal growth.

Social learning and action understanding in human observers: contributions of sensori-motor constraints and prior information

The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Electrochemical sensing strategies for the detection of interactions between biological macromolecules

Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal, enabling the development of cheap, small, portable and simple devices, that allow multiplex and real-time detection. At the same time nanobiotechnology is drastically revolutionizing the biosensors development and different transduction strategies exploit concepts developed in these field to simplify the analysis operations for operators and end users, offering higher specificity, higher sensitivity, higher operational stability, integrated sample treatments and shorter analysis time. The aim of this PhD work has been the application of nanobiotechnological strategies to electrochemical biosensors for the detection of biological macromolecules. Specifically, one project was focused on the application of a DNA nanotechnology called hybridization chain reaction (HCR), to amplify the hybridization signal in an electrochemical DNA biosensor. Another project on which the research activity was focused concerns the development of an electrochemical biosensor based on a biological model membrane anchored to a solid surface (tBLM), for the recognition of interactions between the lipid membrane and different types of target molecules.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

New techniques for the remote sensing of foliar nitrogen concentration in forest ecosystems.

During my Doctoral study I researched about the remote detection of canopy N concentration in forest stands, its potentials and problems, under many overlapping perspectives. The study consisted of three parts. In S. Rossore 2000 dataset analysis, I tested regressions between N concentration and NIR reflectances derived from different sources (field samples, airborne and satellite sensors). The analysis was further expanded using a larger dataset acquired in year 2009 as part of a new campaign funded by the ESA. In both cases, a good correlation was observed between Landsat NIR, using both TM (2009) and ETM+ (2000) imagery, and N concentration measured by a CHN elemental analyzer. Concerning airborne sensors I did not obtain the same good results, mainly because of the large FOV of the two instruments, and to the anisotropy of vegetation reflectance. We also tested the relation between ground based ASD measures and nitrogen concentration, obtaining really good results. Thus, I decided to expand my study to the regional level, focusing only on field and satellite measures. I analyzed a large dataset for the whole of Catalonia, Spain; MODIS imagery was used, in consideration of its spectral characteristics and despite its rather poor spatial resolution. Also in this case a regression between nitrogen concentration and reflectances was found, but not so good as in previous experiences. Moreover, vegetation type was found to play an important role in the observed relationship. We concluded that MODIS is not the most suitable satellite sensor in realities like Italy and Catalonia, which present a patchy and inhomogeneous vegetation cover; so it could be utilized for the parameterization of eco-physiological and biogeochemical models, but not for really local nitrogen estimate. Thus multispectral sensors similar to Landsat Thematic Mapper, with better spatial resolution, could be the most appropriate sensors to estimate N concentration.