Frequency adjustable MEMS vibration energy harvester

Ambient mechanical vibrations offer an attractive solution for powering the wireless sensor nodes of the emerging "Internet-of-Things". However, the wide-ranging variability of the ambient vibration frequencies pose a significant challenge to the efficient transduction of vibration into usable electrical energy. This work reports the development of a MEMS electromagnetic vibration energy harvester where the resonance frequency of the oscillator can be adjusted or tuned to adapt to the ambient vibrational frequency. Micro-fabricated silicon spring and double layer planar micro-coils along with sintered NdFeB micro-magnets are used to construct the electromagnetic transduction mechanism. Furthermore, another NdFeB magnet is adjustably assembled to induce variable magnetic interaction with the transducing magnet, leading to significant change in the spring stiffness and resonance frequency. Finite element analysis and numerical simulations exhibit substantial frequency tuning range (25% of natural resonance frequency) by appropriate adjustment of the repulsive magnetic interaction between the tuning and transducing magnet pair. This demonstrated method of frequency adjustment or tuning have potential applications in other MEMS vibration energy harvesters and micromechanical oscillators.

Privacy matters: issues within mechatronics

As mechatronic devices and components become increasingly integrated with and within wider systems concepts such as Cyber-Physical Systems and the Internet of Things, designer engineers are faced with new sets of challenges in areas such as privacy. The paper looks at the current, and potential future, of privacy legislation, regulations and standards and considers how these are likely to impact on the way in which mechatronics is perceived and viewed. The emphasis is not therefore on technical issues, though these are brought into consideration where relevant, but on the soft, or human centred, issues associated with achieving user privacy.

Sviluppo di YouCrowd: una piattaforma per campagne mobile crowdsensing on-demand

Con il termine "crowdsensing" si intende una tecnica in cui un folto gruppo di individui aventi dispositivi mobili acquisiscono e condividono dati di natura diversa in maniera collettiva, al fine di estrarre informazioni utili. Il concetto di Mobile Crowdsensing è molto recente e derivante dalle ultime innovazioni tecnologiche in materia di connettività online e cattura di dati di vario genere; pertanto non si trova attualmente una vera e propria applicazione in campo reale, la modellazione solo teorica e fin troppo specifica pone un limite alla conoscenza di un ambito che può rivelarsi molto utile ai fini di ricerca. YouCrowd è un piattaforma web che va ad implementare un sistema di crowdsourcing completo, in grado di leggere dati dai numerosi sensori di uno smartphone e condividerli, al fine di ottenere una remunerazione per gli utenti che completano una campagna. La web application vede la sua implementazione di base supportata da NodeJS e si configura come una piattaforma dinamica che varia la propria interfaccia con l'utente in base alle richieste di dati da parte degli administrators. Il test di YouCrowd ha coinvolto un buon numero di partecipanti più o meno esperti nell'utilizzo degli strumenti informatici, rivelando delle buone prestazioni in relazione alla difficoltà del task e alle prestazioni del device in test.

Embedded systems and advanced signal processing for Acousto- Ultrasonic Inspections

Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) are becoming essential in many application contexts, e.g. civil, industrial, aerospace etc., to reduce structures maintenance costs and improve safety. Conventional inspection methods typically exploit bulky and expensive instruments and rely on highly demanding signal processing techniques. The pressing need to overcome these limitations is the common thread that guided the work presented in this Thesis. In the first part, a scalable, low-cost and multi-sensors smart sensor network is introduced. The capability of this technology to carry out accurate modal analysis on structures undergoing flexural vibrations has been validated by means of two experimental campaigns. Then, the suitability of low-cost piezoelectric disks in modal analysis has been demonstrated. To enable the use of this kind of sensing technology in such non conventional applications, ad hoc data merging algorithms have been developed. In the second part, instead, imaging algorithms for Lamb waves inspection (namely DMAS and DS-DMAS) have been implemented and validated. Results show that DMAS outperforms the canonical Delay and Sum (DAS) approach in terms of image resolution and contrast. Similarly, DS-DMAS can achieve better results than both DMAS and DAS by suppressing artefacts and noise. To exploit the full potential of these procedures, accurate group velocity estimations are required. Thus, novel wavefield analysis tools that can address the estimation of the dispersion curves from SLDV acquisitions have been investigated. An image segmentation technique (called DRLSE) was exploited in the k-space to draw out the wavenumber profile. The DRLSE method was compared with compressive sensing methods to extract the group and phase velocity information. The validation, performed on three different carbon fibre plates, showed that the proposed solutions can accurately determine the wavenumber and velocities in polar coordinates at multiple excitation frequencies.

Grant-free protocols for massive multiple access

In next generation Internet-of-Things, the overhead introduced by grant-based multiple access protocols may engulf the access network as a consequence of the proliferation of connected devices. Grant-free access protocols are therefore gaining an increasing interest to support massive multiple access. In addition to scalability requirements, new demands have emerged for massive multiple access, including latency and reliability. The challenges envisaged for future wireless communication networks, particularly in the context of massive access, include: i) a very large population size of low power devices transmitting short packets; ii) an ever-increasing scalability requirement; iii) a mild fixed maximum latency requirement; iv) a non-trivial requirement on reliability. To this aim, we suggest the joint utilization of grant-free access protocols, massive MIMO at the base station side, framed schemes to let the contention start and end within a frame, and succesive interference cancellation techniques at the base station side. In essence, this approach is encapsulated in the concept of coded random access with massive MIMO processing. These schemes can be explored from various angles, spanning the protocol stack from the physical (PHY) to the medium access control (MAC) layer. In this thesis, we delve into both of these layers, examining topics ranging from symbol-level signal processing to succesive interference cancellation-based scheduling strategies. In parallel with proposing new schemes, our work includes a theoretical analysis aimed at providing valuable system design guidelines. As a main theoretical outcome, we propose a novel joint PHY and MAC layer design based on density evolution on sparse graphs.

Mechanical behaviour and durability assessment of Fibre Reinforced Cementitious Matrix (FRCM) strengthening systems.

In recent years, the seismic vulnerability of existing masonry buildings has been underscored by the destructive impacts of earthquakes. Therefore, Fibre Reinforced Cementitious Matrix (FRCM) retrofitting systems have gained prominence due to their high strength-to-weight ratio, compatibility with substrates, and potential reversibility. However, concerns linger regarding the durability of these systems when subjected to long-term environmental conditions. This doctoral dissertation addressed these concerns by studying the effects of mild temperature variations on three FRCM systems, featuring basalt, glass, and aramid fibre textiles with lime-based mortar matrices. The study subjected various specimens, including mortar triplets, bare textile specimens, FRCM coupons, and single-lap direct shear wallets, to thermal exposure. A novel approach utilizing embedded thermocouple sensors facilitated efficient monitoring and active control of the conditioning process. A shift in the failure modes was obtained in the single lap-direct shear tests, alongside a significant impact on tensile capacity for both textiles and FRCM coupons. Subsequently, bond tests results were used to indirectly calibrate an analytical approach based on mode-II fracture mechanics. A comparison between Cohesive Material Law (CML) functions at various temperatures was conducted for each of the three systems, demonstrating a good agreement between the analytical model and experimental curves. Furthermore, the durability in alkaline environment of two additional FRCM systems, characterized by basalt and glass fibre textiles with lime-based mortars, was studied through an extensive experimental campaign. Tests conducted on single yarn and textile specimens after exposure at different durations and temperatures revealed a significant impact on tensile capacity. Additionally, FRCM coupons manufactured with conditioned textile were tested to understand the influence of aged textile and curing environment on the final tensile behavior. These results contributed significantly to the existing knowledge on FRCM systems and could be used to develop a standardized alkaline testing protocol, still lacking in the scientific literature.

6G enabled IoV scenarios with distributed intelligence mechanisms

The Internet of Vehicles (IoV) paradigm has emerged in recent times, where with the support of technologies like the Internet of Things and V2X , Vehicular Users (VUs) can access different services through internet connectivity. With the support of 6G technology, the IoV paradigm will evolve further and converge into a fully connected and intelligent vehicular system. However, this brings new challenges over dynamic and resource-constrained vehicular systems, and advanced solutions are demanded. This dissertation analyzes the future 6G enabled IoV systems demands, corresponding challenges, and provides various solutions to address them. The vehicular services and application requests demands proper data processing solutions with the support of distributed computing environments such as Vehicular Edge Computing (VEC). While analyzing the performance of VEC systems it is important to take into account the limited resources, coverage, and vehicular mobility into account. Recently, Non terrestrial Networks (NTN) have gained huge popularity for boosting the coverage and capacity of terrestrial wireless networks. Integrating such NTN facilities into the terrestrial VEC system can address the above mentioned challenges. Additionally, such integrated Terrestrial and Non-terrestrial networks (T-NTN) can also be considered to provide advanced intelligent solutions with the support of the edge intelligence paradigm. In this dissertation, we proposed an edge computing-enabled joint T-NTN-based vehicular system architecture to serve VUs. Next, we analyze the terrestrial VEC systems performance for VUs data processing problems and propose solutions to improve the performance in terms of latency and energy costs. Next, we extend the scenario toward the joint T-NTN system and address the problem of distributed data processing through ML-based solutions. We also proposed advanced distributed learning frameworks with the support of a joint T-NTN framework with edge computing facilities. In the end, proper conclusive remarks and several future directions are provided for the proposed solutions.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

Progettazione e simulazione di un attacco sniffing su un dispositivo wearable

Oggigiorno, grazie al progresso tecnologico nel settore informatico e alla vasta diffusione dei dispositivi mobili all'interno del mercato mondiale, numerose sono le persone che utilizzando questi prodotti all'interno della vita di tutti giorni e.g. smartphone, smartwatch, smartband, auricolari, tablet, ecc. Per poter utilizzare questi dispositivi, spesso è necessario l'impiego di applicazioni apposite installate sui cellulari di ultima generazione e collegate ai dispositivi che permettono il controllo, la gestione e la raccolta dei dati relativo all'oggetto in questione. Oltre a facilitare le attività giornaliere, questi programmi, potrebbero causare dei problemi agli utenti a causa della ridotta o mancata sicurezza, poiché le informazioni personali come credenziali d'accesso, dati salutistici oppure quelli inerenti ai metodi di pagamento possono essere soggetti ad attacchi informatici. Questa tesi consiste nell'elaborazione di un software composto da un'applicazione Android, uno script Batch e dall'uso di programmi di terze parti, per poter effettuare la simulazione di un attacco sniffing in modo da poter intercettare i dati trasmessi, quali credenziali di accesso, OTP, tramite la tecnologia Bluetooth Low Energy.

Trasformazione digitale nei processi di misura e fatturazione - il caso azienda Alfa

Con il lancio di nuove applicazioni tecnologiche come l'Internet of Things, Big Data, Cloud computing e tecnologie mobili che stanno accelerando in maniera spropositata la velocità di cambiamento, i comportamenti, le abitudini e i modi di vivere sono completamente mutati nel favorire un mondo di tecnologie digitali che agevolino le operazioni quotidiane. Questi progressi stanno velocemente cambiando il modo in cui le aziende fanno business, con grandi ripercussioni in tutto quello che è il contesto aziendale, ma non solo. L’avvento della Digital Transformation ha incrementato questi fenomeni e la si potrebbe definire come causa scatenante di tutti i mutamenti che stiamo vivendo. La velocità e l’intensità del cambiamento ha effetti disruptive rispetto al passato, colpendo numerosi settori economici ed abitudini dei consumatori. L’obiettivo di questo elaborato è di analizzare la trasformazione digitale applicata al caso dell’azienda Alfa, comprendendone le potenzialità. In particolare, si vogliono studiare i principali risvolti portati da tale innovazione, le più importanti iniziative adottate in merito alle nuove tecnologie implementate e i benefici che queste portano in campo strategico, di business e cultura aziendale.

Towards a Smart Campus Digital Twin: Promoting Awareness and Sustainability Through Wayfinding and Real-Time Environmental Data

The newly inaugurated Navile District of the University of Bologna is a complex created along the Navile canal, that now houses various teaching and research activities for the disciplines of Chemistry, Industrial Chemistry, Pharmacy, Biotechnology and Astronomy. A Building Information Modeling system (BIM) gives staff of the Navile campus several ways to monitor buildings in the complex throughout their life cycle, one of which is the ability to access real-time environmental data such as room temperature, humidity, air composition, and more, thereby simplifying operations like finding faults and optimizing environmental resource usage. But smart features at Navile are not only available to the staff: AlmaMap Navile is a web application, whose development is documented in this thesis, that powers the public touch kiosks available throughout the campus, offering maps of the district and indications on how to reach buildings and spaces. Even if these two systems, BIM and AlmaMap, don't seem to have many similarities, they share the common intent of promoting awareness for informed decision making in the campus, and they do it while relying on web standards for communication. This opens up interesting possibilities, and is the idea behind AlmaMap Navile 2.0, an app that interfaces with the BIM system and combines real-time sensor data with a comfort calculation algorithm, giving users the ability not just to ask for directions to a space, but also to see its comfort level in advance and, should they want to, check environmental measurements coming from each sensor in a granular manner. The end result is a first step towards building a smart campus Digital Twin, that can support all the people who are part of the campus life in their daily activities, improving their efficiency and satisfaction, giving them the ability to make informed decisions, and promoting awareness and sustainability.

Shear bond strength of self-etch and total-etch bonding systems at different dentin depths

The purpose of this study was to evaluate the dentin shear bond strength of four adhesive systems (Adper Single Bond 2, Adper Prompt L-Pop, Magic Bond DE and Self Etch Bond) in regards to buccal and lingual surfaces and dentin depth. Forty extracted third molars had roots removed and crowns bisected in the mesiodistal direction. The buccal and lingual surfaces were fixed in a PVC/acrylic resin ring and were divided into buccal and lingual groups assigned to each selected adhesive. The same specimens prepared for the evaluation of superficial dentin shear resistance were used to evaluate the different depths of dentin. The specimens were identified and abraded at depths of 0.5, 1.0, 1.5 and 2.0 mm. Each depth was evaluated by ISO TR 11405 using an EMIC-2000 machine regulated at 0.5 mm/min with a 200 Kgf load cell. We performed statistical analyses on the results (ANOVA, Tukey and Scheffé tests). Data revealed statistical differences (p < 0.01) in the adhesive and depth variation as well as adhesive/depth interactions. The Adper Single Bond 2 demonstrated the highest mean values of shear bond strength. The Prompt L-Pop product, a self-etching adhesive, revealed higher mean values compared with Magic Bond DE and Self Etch Bond adhesives, a total and self-etching adhesive respectively. It may be concluded that the shear bond strength of dentin is dependent on material (adhesive system), substrate depth and adhesive/depth interaction.

The role of magnetic reconnection on jet/accretion disk systems

Context. It was proposed earlier that the relativistic ejections observed in microquasars could be produced by violent magnetic reconnection episodes at the inner disk coronal region (de Gouveia Dal Pino & Lazarian 2005). Aims. Here we revisit this model, which employs a standard accretion disk description and fast magnetic reconnection theory, and discuss the role of magnetic reconnection and associated heating and particle acceleration in different jet/disk accretion systems, namely young stellar objects (YSOs), microquasars, and active galactic nuclei (AGNs). Methods. In microquasars and AGNs, violent reconnection episodes between the magnetic field lines of the inner disk region and those that are anchored in the black hole are able to heat the coronal/disk gas and accelerate the plasma to relativistic velocities through a diffusive first-order Fermi-like process within the reconnection site that will produce intermittent relativistic ejections or plasmons. Results. The resulting power-law electron distribution is compatible with the synchrotron radio spectrum observed during the outbursts of these sources. A diagram of the magnetic energy rate released by violent reconnection as a function of the black hole (BH) mass spanning 10(9) orders of magnitude shows that the magnetic reconnection power is more than sufficient to explain the observed radio luminosities of the outbursts from microquasars to low luminous AGNs. In addition, the magnetic reconnection events cause the heating of the coronal gas, which can be conducted back to the disk to enhance its thermal soft X-ray emission as observed during outbursts in microquasars. The decay of the hard X-ray emission right after a radio flare could also be explained in this model due to the escape of relativistic electrons with the evolving jet outburst. In the case of YSOs a similar magnetic configuration can be reached that could possibly produce observed X-ray flares in some sources and provide the heating at the jet launching base, but only if violent magnetic reconnection events occur with episodic, very short-duration accretion rates which are similar to 100-1000 times larger than the typical average accretion rates expected for more evolved (T Tauri) YSOs.

CHARACTERIZATION OF EXPONENTIAL DIVERGENCE OF THE KALMAN FILTER FOR TIME-VARYING SYSTEMS

This paper studies semistability of the recursive Kalman filter in the context of linear time-varying (LTV), possibly nondetectable systems with incorrect noise information. Semistability is a key property, as it ensures that the actual estimation error does not diverge exponentially. We explore structural properties of the filter to obtain a necessary and sufficient condition for the filter to be semistable. The condition does not involve limiting gains nor the solution of Riccati equations, as they can be difficult to obtain numerically and may not exist. We also compare semistability with the notions of stability and stability w.r.t. the initial error covariance, and we show that semistability in a sense makes no distinction between persistent and nonpersistent incorrect noise models, as opposed to stability. In the linear time invariant scenario we obtain algebraic, easy to test conditions for semistability and stability, which complement results available in the context of detectable systems. Illustrative examples are included.

Evidences of turbulent mixing in multi-pumping flow systems

Multi-pumping flow systems exploit pulsed flows delivered by Solenoid pumps. Their improved performance rely on the enhanced radial mass transport inherent to the pulsed flow, which is a consequence of the establishment of vortices thus a tendency towards turbulent mixing. This paper presents several evidences of turbulent mixing in relation to pulsed flows. such as recorded peak shape, establishment of fluidized beds, exploitation of flow reversal, implementation of relatively slow chemical reactions and/or heating of the reaction medium. In addition, Reynolds number associated with the GO period of a pulsed flow is estimated and photographic images of dispersing samples flowing under laminar regime and pulsed flow conditions are presented. (C) 2009 Elsevier B.V. All rights reserved.