Sensor Data Fusion e applicazioni

Un trattato che illustra tutto quello che riguarda il Sensor Data Fusion sin dagli strumenti basilari fino alle applicazioni di specializzate

From data to applications in the Internet of Things

Con la crescita in complessità delle infrastrutture IT e la pervasività degli scenari di Internet of Things (IoT) emerge il bisogno di nuovi modelli computazionali basati su entità autonome capaci di portare a termine obiettivi di alto livello interagendo tra loro grazie al supporto di infrastrutture come il Fog Computing, per la vicinanza alle sorgenti dei dati, e del Cloud Computing per offrire servizi analitici complessi di back-end in grado di fornire risultati per milioni di utenti. Questi nuovi scenarii portano a ripensare il modo in cui il software viene progettato e sviluppato in una prospettiva agile. Le attività dei team di sviluppatori (Dev) dovrebbero essere strettamente legate alle attività dei team che supportano il Cloud (Ops) secondo nuove metodologie oggi note come DevOps. Tuttavia, data la mancanza di astrazioni adeguata a livello di linguaggio di programmazione, gli sviluppatori IoT sono spesso indotti a seguire approcci di sviluppo bottom-up che spesso risulta non adeguato ad affrontare la compessità delle applicazione del settore e l'eterogeneità dei compomenti software che le formano. Poichè le applicazioni monolitiche del passato appaiono difficilmente scalabili e gestibili in un ambiente Cloud con molteplici utenti, molti ritengono necessaria l'adozione di un nuovo stile architetturale, in cui un'applicazione dovrebbe essere vista come una composizione di micro-servizi, ciascuno dedicato a uno specifica funzionalità applicativa e ciascuno sotto la responsabilità di un piccolo team di sviluppatori, dall'analisi del problema al deployment e al management. Poichè al momento non si è ancora giunti a una definizione univoca e condivisa dei microservices e di altri concetti che emergono da IoT e dal Cloud, nè tantomento alla definzione di linguaggi sepcializzati per questo settore, la definzione di metamodelli custom associati alla produzione automatica del software di raccordo con le infrastrutture potrebbe aiutare un team di sviluppo ad elevare il livello di astrazione, incapsulando in una software factory aziendale i dettagli implementativi. Grazie a sistemi di produzione del sofware basati sul Model Driven Software Development (MDSD), l'approccio top-down attualmente carente può essere recuperato, permettendo di focalizzare l'attenzione sulla business logic delle applicazioni. Nella tesi viene mostrato un esempio di questo possibile approccio, partendo dall'idea che un'applicazione IoT sia in primo luogo un sistema software distribuito in cui l'interazione tra componenti attivi (modellati come attori) gioca un ruolo fondamentale.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

The secret life of software applications

One of the most undervalued problems by smartphone users is the security of data on their mobile devices. Today smartphones and tablets are used to send messages and photos and especially to stay connected with social networks, forums and other platforms. These devices contain a lot of private information like passwords, phone numbers, private photos, emails, etc. and an attacker may choose to steal or destroy this information. The main topic of this thesis is the security of the applications present on the most popular stores (App Store for iOS and Play Store for Android) and of their mechanisms for the management of security. The analysis is focused on how the architecture of the two systems protects users from threats and highlights the real presence of malware and spyware in their respective application stores. The work described in subsequent chapters explains the study of the behavior of 50 Android applications and 50 iOS applications performed using network analysis software. Furthermore, this thesis presents some statistics about malware and spyware present on the respective stores and the permissions they require. At the end the reader will be able to understand how to recognize malicious applications and which of the two systems is more suitable for him. This is how this thesis is structured. The first chapter introduces the security mechanisms of the Android and iOS platform architectures and the security mechanisms of their respective application stores. The Second chapter explains the work done, what, why and how we have chosen the tools needed to complete our analysis. The third chapter discusses about the execution of tests, the protocol followed and the approach to assess the “level of danger” of each application that has been checked. The fourth chapter explains the results of the tests and introduces some statistics on the presence of malicious applications on Play Store and App Store. The fifth chapter is devoted to the study of the users, what they think about and how they might avoid malicious applications. The sixth chapter seeks to establish, following our methodology, what application store is safer. In the end, the seventh chapter concludes the thesis.

Morphological and optical properties of SiON thin films for photovoltaic applications

In the last years technologies related to photovoltaic energy have rapidly developed and the interest on renewable energy power source substantially increased. In particular, cost reduction and appropriate feed-in tariff contributed to the increase of photovoltaic installation, especially in Germany and Italy. However, for several technologies, the observed experimental efficiency of solar cells is still far from the theoretical maximum efficiency, and thus there is still room for improvement. In this framework the research and development of new materials and new solar devices is mandatory. In this thesis the morphological and optical properties of thin films of nanocrystalline silicon oxynitride (nc-SiON) have been investigated. This material has been studied in view of its application in Si based heterojunction solar cells (HIT). Actually, a-Si:H is used now in these cells as emitter layer. Amorphous SiO_x N_y has already shown excellent properties, such as: electrical conductivity, optical energy gap and transmittance higher than the ones of a-Si:H. Nc-SiO_x N_y has never been investigated up to now, but its properties can surpass the ones of amorphous SiON. The films of nc-SiON have been deposited at the University of Konstanz (Germany). The properties of these films have been studied using of atomic force microscopy and optical spectroscopy methods. This material is highly complex as it is made by different coexisting phases. The main purpose of this thesis is the development of methods for the analyses of morphological and optical properties of nc-SiON and the study of the reliability of those methods to the measurement of the characteristics of these silicon films. The collected data will be used to understand the evolution of the properties of nc-SiON, as a function of the deposition parameters. The results here obtained show that nc-SiON films have better properties with respect to both a-Si:H and a-SiON, i. e. higher optical band-gap and transmittance. In addition, the analysis of the variation of the observed properties as a function of the deposition parameters allows for the optimization of deposition conditions for obtaining optimal efficiency of a HIT cell with SiON layer.

Chemical composition modification of casting aluminium alloys for engine applications

The research activities were focused on evaluating the effect of Mo addition to mechanical properties and microstructure of A354 aluminium casting alloy. Samples, with increasing amount of Mo, were produced and heat treated. After heat treatment and exposition to high temperatures samples underwent microstructural and chemical analyses, hardness and tensile tests. The collected data led to the optimization of both casting parameters, for obtaining a homogeneous Mo distribution in the alloy, and heat treatment parameters, allowing the formation of Mo based strengthening precipitates stable at high temperature. Microstructural and chemical analyses highlighted how Mo addition in percentage superior to 0.1% wt. can modify the silicon eutectic morphology and hinder the formation of iron based β intermetallics. High temperature exposure curves, instead, showed that after long exposition hardness is slightly influenced by heat treatment while the effect of Mo addition superior to 0,3% is negligible. Tensile tests confirmed that the addition of 0.3%wt Mo induces an increase of about 10% of ultimate tensile strength after high temperature exposition (250°C for 100h) while heat treatments have slight influence on mechanical behaviour. These results could be exploited for developing innovative heat treatment sequence able to reduce residual stresses in castings produced with A354 modified with Mo.