Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.

Pavement and alignment design of a new rural road in the province of Bologna

This thesis aims to give a general view of pavement types all over the world, by showing the different characteristics of each one and its different life steps starting from construction, passing by maintenance and arriving until recycling phase. The flexible pavement took the main part of this work because it has been used in the last part of this thesis to design a project of a rural road. This project is located in the province of Bologna-Italy (‘Comune di Argelato’, 26 km in the north of Bologna), and has 5677, 81 m of length. A pavement design was made using the program BISAR 3.0 and a fatigue life study was made, also, in order to estimate the number of loads (in terms of heavy vehicles axle) to cause road’s failure . An alignment design was made for this project and a safety study was established in order to check if the available sight distance at curves respects the safety norms or not, by comparing it to the stopping sight distance. Different technical sheets are demonstrated and several cases are discussed in order to clarify the main design principles and underline the main hazardous cases to be avoided especially at intersection. This latter, its type’s choice depends on several factors in order to make the suitable design according to the environmental data. At this part of the road, the safety is a primordial point due to the high accident rate in this zone. For this reason, different safety aspects are discussed especially at roundabouts, signalized intersections, and also some other common intersection types. The design and the safety norms are taken with reference to AASHTO (American Association of State Highway and Transportation Officials), ACT (Transportation Association of Canada), and also according to Italian norms (Decreto Ministeriale delle Starde).

Early Warning For Large Earthquakes: Observations, Models and Real-Time Data Analysis

This thesis is a collection of works focused on the topic of Earthquake Early Warning, with a special attention to large magnitude events. The topic is addressed from different points of view and the structure of the thesis reflects the variety of the aspects which have been analyzed. The first part is dedicated to the giant, 2011 Tohoku-Oki earthquake. The main features of the rupture process are first discussed. The earthquake is then used as a case study to test the feasibility Early Warning methodologies for very large events. Limitations of the standard approaches for large events arise in this chapter. The difficulties are related to the real-time magnitude estimate from the first few seconds of recorded signal. An evolutionary strategy for the real-time magnitude estimate is proposed and applied to the single Tohoku-Oki earthquake. In the second part of the thesis a larger number of earthquakes is analyzed, including small, moderate and large events. Starting from the measurement of two Early Warning parameters, the behavior of small and large earthquakes in the initial portion of recorded signals is investigated. The aim is to understand whether small and large earthquakes can be distinguished from the initial stage of their rupture process. A physical model and a plausible interpretation to justify the observations are proposed. The third part of the thesis is focused on practical, real-time approaches for the rapid identification of the potentially damaged zone during a seismic event. Two different approaches for the rapid prediction of the damage area are proposed and tested. The first one is a threshold-based method which uses traditional seismic data. Then an innovative approach using continuous, GPS data is explored. Both strategies improve the prediction of large scale effects of strong earthquakes.

Advanced modelling of time domain electromagnetic data with updated hydrogeological interpretations

Several countries have acquired, over the past decades, large amounts of area covering Airborne Electromagnetic data. Contribution of airborne geophysics has dramatically increased for both groundwater resource mapping and management proving how those systems are appropriate for large-scale and efficient groundwater surveying. We start with processing and inversion of two AEM dataset from two different systems collected over the Spiritwood Valley Aquifer area, Manitoba, Canada respectively, the AeroTEM III (commissioned by the Geological Survey of Canada in 2010) and the “Full waveform VTEM” dataset, collected and tested over the same survey area, during the fall 2011. We demonstrate that in the presence of multiple datasets, either AEM and ground data, due processing, inversion, post-processing, data integration and data calibration is the proper approach capable of providing reliable and consistent resistivity models. Our approach can be of interest to many end users, ranging from Geological Surveys, Universities to Private Companies, which are often proprietary of large geophysical databases to be interpreted for geological and\or hydrogeological purposes. In this study we deeply investigate the role of integration of several complimentary types of geophysical data collected over the same survey area. We show that data integration can improve inversions, reduce ambiguity and deliver high resolution results. We further attempt to use the final, most reliable output resistivity models as a solid basis for building a knowledge-driven 3D geological voxel-based model. A voxel approach allows a quantitative understanding of the hydrogeological setting of the area, and it can be further used to estimate the aquifers volumes (i.e. potential amount of groundwater resources) as well as hydrogeological flow model prediction. In addition, we investigated the impact of an AEM dataset towards hydrogeological mapping and 3D hydrogeological modeling, comparing it to having only a ground based TEM dataset and\or to having only boreholes data.

Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

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

The application of a new psychotherapeutic strategy for enhancing eudaimonic well-being in children with mood and anxiety disorders

The aim of the dissertation was to test the feasibility of a new psychotherapeutic protocol for treating children and adolescents with mood and anxiety disorders: Child-Well-Being Therapy (CWBT). It originates from adult Well-Being Therapy protocol (WBT) and represents a conceptual innovation for treating affective disorders. WBT is based on the multidimensional model of well-being postulated by Ryff (eudaimonic perspective), in sequential combination with cognitive-behavioral therapy (CBT). Results showed that eudaimonic well-being was impaired in children with affective disorders in comparison with matched healthy students. A first open investigation aimed at exploring the feasibility of a 8-session CWBT protocol in a group of children with emotional and behavioural disorders has been implemented. Data showed how CWBT resulted associated to symptoms reduction, together with the decrease of externalizing problems, maintained at 1-year follow-up. CWBT triggered also an improvement in psychological well-being as well as an increasing flourishing trajectory over time. Subsequently, a modified and extended version of CWBT (12-sessions) has been developed and then tested in a controlled study with 34 patients (8 to 16 years) affected by mood and anxiety disorders. They were consecutively randomized into 3 different groups: CWBT, CBT, 6-month waiting list (WL). Both treatments resulted effective in decreasing distress and in improving well-being. Moreover, CWBT was associated with higher improvement in anxiety and showed a greater recovery rate (83%) than CBT (54%). Both groups maintained beneficial effects and CWBT group displayed a lower level of distress as well as a higher positive trend in well-being scores over time. Findings need to be interpret with caution, because of study limitations, however important clinical implications emerged. Further investigations should determine whether the sequential integration of well-being and symptom-oriented strategies could play an important role in children and adolescents’ psychotherapeutic options, fostering a successful adaptation to adversities during the growth process.

In vivo evaluation of the translations of the gleno-humeral joint using Magnetic resonance imaging

Gleno-humeral joint (GHJ) is the most mobile joint of the human body. This is related to theincongr uence between the large humeral head articulating with the much smaller glenoid (ratio 3:1). The GHJ laxity is the ability of the humeral head to be passively translated on the glenoid fossa and, when physiological, it guarantees the normal range of motion of the joint. Three-dimensional GHJ linear displacements have been measured, both in vivo and in vitro by means of different instrumental techniques. In vivo gleno-humeral displacements have been assessed by means of stereophotogrammetry, electromagnetic tracking sensors, and bio-imaging techniques. Both stereophotogrammetric systems and electromagnetic tracking devices, due to the deformation of the soft tissues surrounding the bones, are not capable to accurately assess small displacements, such as gleno-humeral joint translations. The bio-imaging techniques can ensure for an accurate joint kinematic (linear and angular displacement) description, but, due to the radiation exposure, most of these techniques, such as computer tomography or fluoroscopy, are invasive for patients. Among the bioimaging techniques, an alternative which could provide an acceptable level of accuracy and that is innocuous for patients is represented by magnetic resonance imaging (MRI). Unfortunately, only few studies have been conducted for three-dimensional analysis and very limited data is available in situations where preset loads are being applied. The general aim of this doctoral thesis is to develop a non-invasive methodology based on open-MRI for in-vivo evaluation of the gleno-humeral translation components in healthy subjects under the application of external loads.

Software per l'analisi di Big Data su più livelli e sua applicazione a tracce di Google

Con l'avanzare della tecnologia, i Big Data hanno assunto un ruolo importante. In questo lavoro è stato implementato, in linguaggio Java, un software volto alla analisi dei Big Data mediante R e Hadoop/MapReduce. Il software è stato utilizzato per analizzare le tracce rilasciate da Google, riguardanti il funzionamento dei suoi data center.

Fog escaping: un'applicazione di mobile data CrowdSourcing per il supporto alla mobilità veicolare

In questa Tesi di laurea, si è affrontato il problema della mobilità veicolare in caso di nebbie. Si è quindi sviluppato un prototipo con architettura Client-Server, che si è soffermato maggiormente sull’analisi dei dati per la creazione di un percorso alternativo. Si è preso in considerazione il sistema operativo mobile di Apple, iOS7 che rappresenta uno dei Sistemi Operativi mobili maggiormente presenti sul mercato oggigiorno e che possiede un buon bacino di utenze. La parte Server è stata sviluppata secondo l’architettura REST; è presente un Server HTTP che riceve richieste e risponde in modo adeguato ai Client tramite lo scambio bidirezionale di dati in formato JSON. Nella parte Server è inclusa la base di dati: un componente molto importante poiché implementa al suo interno, parte della logica di Sistema tramite stored procedure. La parte Client è un’applicazione per dispositivi iPad e iPhone chiamata Fog Escaping; essa è stata sviluppata secondo il pattern MVC (Model- View-Controller). Fog Escaping implementa un algoritmo Greedy di ricerca del percorso alternativo, che può essere utilizzato per diverse tipologie di applicazioni.

Analisi e realizzazione di una piattaforma basate sul Cloud Computing per il trattamento dei Big Data.

L'elaborato introduce i concetti di Big Data, Cloud Computing e le tipologie di paradigmi basati sul calcolo parallelo. Trasformando questi concetti in pratica tramite un caso di studio sui Big Data. Nell'elaborato si spiega l'architettura proposta per l'elaborazione di report in formato pdf. Analaizando in fine i risultati ottenuti.

Linked Data e bibliometriche: un indice di multidisciplinarieta nel Semantic Publishing

Nel presente lavoro si introduce un nuovo indice per la valutazione dei prodotti della ricerca: l'indice di multidisciplinarieta`. Questa nuova metrica puo` essere un interessante parametro di valutazione: il panorama degli studi multidisciplinari e` vasto ed eterogeneo, ed all'interno di questo sono richieste necessarie competenze trasversali. Le attuali metriche adottate nella valutazione di un accademico, di un journal, o di una conferenza non tengono conto di queste situazioni intermedie, e limitano la loro valutazione dell'impatto al semplice conteggio delle citazioni ricevute. Il risultato di tale valutazione consiste in un valore dell'impatto della ricerca senza una connotazione della direzione e della rilevanza di questa nel contesto delle altre discipline. L'indice di multidisciplinarieta` proposto si integrerebbe allora all'interno dell'attuale panorama delle metriche di valutazione della ricerca, offrendo -accanto ad una quantificazione dell'impatto- una quantificazione della varieta` dei contesti disciplinari nei quali si inserisce.

Paleosol-based stratigraphy of late Quaternary deposits from the Po basin, between Bologna and the Po river (Northern Italy)

Stratigraphic studies carried out over the last decades in Italy and elsewhere testify a growing interest in Quaternary deposits and in the influence of climate change on their architecture. The subsurface of the Po Plain, in its topmost portion, is made up of alluvial deposits organized in depositional cycles at different scales. This PhD thesis provides millennial-scale stratigraphic reconstruction of the Late Pleistocene-Holocene deposits beneath the southern Po Plain, based on basin-scale correlation of laterally-extensive buried soil horizons. Far from the aim of characterizing palaeosols from a mineralogical and geochemical point of view, we focused on the physical and stratigraphic significance of these horizons. In the Bologna urban area, which hosts an abundance of stratigraphic data, the correlation between seventeen continuously-cored boreholes led to the identification of five vertically-stacked palaeosol-bounded sequences within the 14C time window. In a wide portion of the alluvial plain north of Bologna, far away from the Apenninic margin and from the Po River, where subsurface stratigraphic architecture is dominated by markedly lenticular sediment bodies, palaeosols revealed to be the only stratigraphic marker of remarkable lateral continuity. These horizons are characterized by peculiar resistance values, which make them easily identifiable via pocket penetration tests. Palaeosols reveal specific geometric relationships with the associated alluvial facies associations, allowing reliable estimates of soil development as a function of alluvial dynamics. With the aid of sixty new radiocarbon dates, a reliable age attribution and likely time intervals of exposure were assigned to each palaeosol. Vertically-stacked palaeosols delimitate short-term depositional cycles, likely related to the major episodes of climatic change of the last 40 ky. Through integration of stratigraphic data with 750 archaeological reports from the Bologna area, the impact of human settlements on depositional and pedogenic processes during the late Holocene was investigated.

Opportunistic Data Gathering and Dissemination in Urban Scenarios

In the era of the Internet of Everything, a user with a handheld or wearable device equipped with sensing capability has become a producer as well as a consumer of information and services. The more powerful these devices get, the more likely it is that they will generate and share content locally, leading to the presence of distributed information sources and the diminishing role of centralized servers. As of current practice, we rely on infrastructure acting as an intermediary, providing access to the data. However, infrastructure-based connectivity might not always be available or the best alternative. Moreover, it is often the case where the data and the processes acting upon them are of local scopus. Answers to a query about a nearby object, an information source, a process, an experience, an ability, etc. could be answered locally without reliance on infrastructure-based platforms. The data might have temporal validity limited to or bounded to a geographical area and/or the social context where the user is immersed in. In this envisioned scenario users could interact locally without the need for a central authority, hence, the claim of an infrastructure-less, provider-less platform. The data is owned by the users and consulted locally as opposed to the current approach of making them available globally and stay on forever. From a technical viewpoint, this network resembles a Delay/Disruption Tolerant Network where consumers and producers might be spatially and temporally decoupled exchanging information with each other in an adhoc fashion. To this end, we propose some novel data gathering and dissemination strategies for use in urban-wide environments which do not rely on strict infrastructure mediation. While preserving the general aspects of our study and without loss of generality, we focus our attention toward practical applicative scenarios which help us capture the characteristics of opportunistic communication networks.

A Semantic-based Framework for Digital Survey of Architectural Heritage

The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.