Optical Wireless Communication for Mobile Platforms

The past few decades have witnessed the widespread adaptation of wireless devices such as cellular phones and Wifi-connected laptops, and demand for wireless communication is expected to continue to increase. Though radio frequency (RF) communication has traditionally dominated in this application space, recent decades have seen an increasing interest in the use of optical wireless (OW) communication to supplement RF communications. In contrast to RF communication technology, OW systems offer the use of largely unregulated electromagnetic spectrum and large bandwidths for communication. They also offer the potential to be highly secure against jamming and eavesdropping. Interest in OW has become especially keen in light of the maturation of light-emitting diode (LED) technology. This maturation, and the consequent emerging ubiquity of LED technology in lighting systems, has motivated the exploration of LEDs for wireless communication purposes in a wide variety of applications. Recent interest in this field has largely focused on the potential for indoor local area networks (LANs) to be realized with increasingly common LED-based lighting systems. We envision the use of LED-based OW to serve as a supplement to RF technology in communication between mobile platforms, which may include automobiles, robots, or unmanned aerial vehicles (UAVs). OW technology may be especially useful in what are known as RF-denied environments, in which RF communication may be prohibited or undesirable. The use of OW in these settings presents major challenges. In contrast to many RF systems, OWsystems that operate at ranges beyond a few meters typically require relatively precise alignment. For example, some laser-based optical wireless communication systems require alignment precision to within small fractions of a degree. This level of alignment precision can be difficult to maintain between mobile platforms. Additionally, the use of OW systems in outdoor settings presents the challenge of interference from ambient light, which can be much brighter than any LED transmitter. This thesis addresses these challenges to the use of LED-based communication between mobile platforms. We propose and analyze a dual-link LED-based system that uses one link with a wide transmission beam and relaxed alignment constraints to support a more narrow, precisely aligned, higher-data-rate link. The use of an optical link with relaxed alignment constraints to support the alignment of a more precisely aligned link motivates our exploration of a panoramic imaging receiver for estimating the range and bearing of neighboring nodes. The precision of such a system is analyzed and an experimental system is realized. Finally, we present an experimental prototype of a self-aligning LED-based link.

MEMS SENSOR PLATFORMS FOR IN SITU CHARACTERIZATION OF LI-ION BATTERY ELECTRODES

Lithium-ion batteries provide high energy density while being compact and light-weight and are the most pervasive energy storage technology powering portable electronic devices such as smartphones, laptops, and tablet PCs. Considerable efforts have been made to develop new electrode materials with ever higher capacity, while being able to maintain long cycle life. A key challenge in those efforts has been characterizing and understanding these materials during battery operation. While it is generally accepted that the repeated strain/stress cycles play a role in long-term battery degradation, the detailed mechanisms creating these mechanical effects and the damage they create still remain unclear. Therefore, development of techniques which are capable of capturing in real time the microstructural changes and the associated stress during operation are crucial for unravelling lithium-ion battery degradation mechanisms and further improving lithium-ion battery performance. This dissertation presents the development of two microelectromechanical systems sensor platforms for in situ characterization of stress and microstructural changes in thin film lithium-ion battery electrodes, which can be leveraged as a characterization platform for advancing battery performance. First, a Fabry-Perot microelectromechanical systems sensor based in situ characterization platform is developed which allows simultaneous measurement of microstructural changes using Raman spectroscopy in parallel with qualitative stress changes via optical interferometry. Evolutions in the microstructure creating a Raman shift from 145 cm−1 to 154 cm−1 and stress in the various crystal phases in the LixV2O5 system are observed, including both reversible and irreversible phase transitions. Also, a unique way of controlling electrochemically-driven stress and stress gradient in lithium-ion battery electrodes is demonstrated using the Fabry-Perot microelectromechanical systems sensor integrated with an optical measurement setup. By stacking alternately stressed layers, the average stress in the stacked electrode is greatly reduced by 75% compared to an unmodified electrode. After 2,000 discharge-charge cycles, the stacked electrodes retain only 83% of their maximum capacity while unmodified electrodes retain 91%, illuminating the importance of the stress gradient within the electrode. Second, a buckled membrane microelectromechanical systems sensor is developed to enable in situ characterization of quantitative stress and microstructure evolutions in a V2O5 lithium-ion battery cathode by integrating atomic force microscopy and Raman spectroscopy. Using dual-mode measurements in the voltage range of the voltage range of 2.8V – 3.5V, both the induced stress (~ 40 MPa) and Raman intensity changes due to lithium cycling are observed. Upon lithium insertion, tensile stress in the V2O5 increases gradually until the α- to ε-phase and ε- to δ-phase transitions occur. The Raman intensity change at 148 cm−1 shows that the level of disorder increases during lithium insertion and progressively recovers the V2O5 lattice during lithium extraction. Results are in good agreement with the expected mechanical behavior and disorder change in V2O5, highlighting the potential of microelectromechanical systems as enabling tools for advanced scientific investigations. The work presented here will be eventually utilized for optimization of thin film battery electrode performance by achieving fundamental understanding of how stress and microstructural changes are correlated, which will also provide valuable insight into a battery performance degradation mechanism.

Estado del arte del IoT aplicado a la geotecnia

69 p.

FREEZE SENSE : sensor IoT para monitorizar la cadena de frío en el transporte y almacenamiento de alimentos

Mantener y asegurar la cadena del frío en el transporte de alimentos perecederos es uno de los aspectos más importantes que deben tener en cuenta las empresas de logística y cadenas de venta al consumidor. Con el control de la cadena del frío se puede asegurar tanto unos mínimos de calidad como de seguridad del producto en cuestión. Para asegurar el cumplimiento de la cadena de frío en el transporte de alimentos (o medicamentos) existen actualmente multitud de sistemas o dispositivos en el mercado que pueden cumplir perfectamente ese papel. Algunos de ellos son sistemas que únicamente informan al operario en destino si se ha producido una ruptura de la cadena del frío sirviendo como control de calidad previo a la venta de los alimentos, pero por el contrario otros sistemas sí que realizan un control exhaustivo de la cadena de frío en tiempo real dando una mayor capacidad de reacción a la empresa logística o cadena de venta para subsanar cuanto antes esa ruptura en la cadena del frío. Es este tipo de sistemas en el que se va a basar este proyecto. Por ello con la ayuda de la arquitectura IoT se mejorarán las principales ventajas que tienen este tipo de sistemas (funcionalidad) y disminuirán o incluso eliminarán las desventajas que tienen este tipo de sistemas, principalmente coste (objetivo más importante del proyecto) y dificultad de instalación.

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Image and video compression play a major role in the world today, allowing the storage and transmission of large multimedia content volumes. However, the processing of this information requires high computational resources, hence the improvement of the computational performance of these compression algorithms is very important. The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based compression algorithm for multimedia contents, namely images, achieving high compression ratios, maintaining good image quality, Rodrigues et al. [2008]. However, in comparison with other existing algorithms, this algorithm takes some time to execute. Therefore, two parallel implementations for GPUs were proposed by Ribeiro [2016] and Silva [2015] in CUDA and OpenCL-GPU, respectively. In this dissertation, to complement the referred work, we propose two parallel versions that run the MMP algorithm in CPU: one resorting to OpenMP and another that converts the existing OpenCL-GPU into OpenCL-CPU. The proposed solutions are able to improve the computational performance of MMP by 3 and 2:7 , respectively. The High Efficiency Video Coding (HEVC/H.265) is the most recent standard for compression of image and video. Its impressive compression performance, makes it a target for many adaptations, particularly for holoscopic image/video processing (or light field). Some of the proposed modifications to encode this new multimedia content are based on geometry-based disparity compensations (SS), developed by Conti et al. [2014], and a Geometric Transformations (GT) module, proposed by Monteiro et al. [2015]. These compression algorithms for holoscopic images based on HEVC present an implementation of specific search for similar micro-images that is more efficient than the one performed by HEVC, but its implementation is considerably slower than HEVC. In order to enable better execution times, we choose to use the OpenCL API as the GPU enabling language in order to increase the module performance. With its most costly setting, we are able to reduce the GT module execution time from 6.9 days to less then 4 hours, effectively attaining a speedup of 45 .

Gesture based IoT light control for smart clothing

In this paper, a smart wireless wristband is proposed. The potential of innovative gesture based interactivity with connected lighting solutions is reviewed. The solution is intended to offer numerous benefits, in terms of ease of use, and enhanced dynamic interactive functionality. A comparative analysis will be carried out between this work and existing solutions. The evolution of lighting and gesture controls will be discussed and an overview of alternative applications will be provided, as part of the critical analysis.

An Overview of IoT and Healthcare

This paper is an overview of some of the implications of IoT on the healthcare field. Due to the increasing of IoT solutions, healthcare cannot be outside of this paradigm. The contribution of this paper is to introduce directions to achieve a global connectivity between the Internet of Things (IoT) and the medical environments. The need to integrate all in a global environment is a huge challenge to all (from electrical engineers to data engineers).This revolution is redesigning the way we see healthcare, from the smallest sensor to the big data collected.

Multifarious tumor-oriented small molecules: development of synthetic methodologies and application for diagnostic platforms

Cancer represents one of the most relevant and widespread diseases in the modern age. In this context, integrin receptors are important for the interactions of cells with extracellular matrix and for the development of both inflammation and carcinogenic phenomena. There are many tricks to improve the bioactivity and receptor selectivity of exogenous ligands; one of these is to integrate the amino acid sequence into a cyclic peptide to restrict its conformational space. Another approach is to develop small peptidomimetic molecules in order to enhance the molecular stability and open the way to versatile synthetic strategies. Starting from isoxazoline-based peptidomimetic molecules we recently reported, in this thesis we are going to present the synthesis of new integrin ligands obtained by modifying or introducing appendages on already reported structures. Initially, we are going to introduce the synthesis of linear and cyclic α-dehydro-β-amino acids as scaffolds for the preparation of bioactive peptidomimetics. Subsequently, we are going to present the construction of small molecule ligands (SMLs) based delivery systems performed starting from a polyfunctionalised isoxazoline scaffold, whose potency towards αVβ3 and α5β1 integrins has already been established by our research group. In the light of these results and due to the necessity to understand the behaviour of a single enantiomer of the isoxazoline-based compounds, the research group decided to synthesise the enantiopure heterocycle using a 1,3-dipolar cycloaddiction approach. Subsequently, we are going to introduce the synthesis of a Reporting Drug Delivery System composed by a carrier, a first spacer, a linker, a self-immolative system, a second spacer and a latent fluorophore. The last part of this work will describe the results obtained during the internship abroad in Prof. Aggarwal’s laboratory at the University of Bristol. The project was focused on the Mycapolyol A synthesis.

Advanced cell culture platforms: methods for drug testing with microfluidics and microstructured devices

Advanced cell cultures are developing rapidly in biomedical research. Nowadays, various approaches and technologies are being used, however, these culturing systems present limitations from increasing complexity, requiring high costs, and not easily customization. We present two versatile and cost-effective methods for developing culturing systems that integrate 3D cell culture and microfluidic platforms. Firstly, for drug screening applications, many high-quality cell spheres of homogeneous size and shape are required. Conventional approaches usually have a dearth of control over the size and geometry of cell spheres and require sample collection and manipulation. To overcome this difficulty, in this study, hundreds of spheroids of several cell lines were generated using multi-well plates that housed our microdevices. Tumor spheroids grow at a uniform rate (in scaffolded or scaffold-free environments) and can be harvested at will. Microscopy imaging are done in real time during or after the culture. After in situ immunostaining, fluorescence imaging can be conducted while keeping the spatial distribution of spheroids in the microwells. Drug effects were successfully observed through viability, growth, and morphologic investigations. Also, we fabricated a microfluidic device suitable for directed and selective cell culture treatments. The microfluidic device was used to reproduce and confirm in vitro investigations carried out using normal culture methods, using a microglia cell line. The device layout and the syringe pump system, entirely designed in our lab, successfully allowed culture growth and medium flow regulation. Solution flows can be finely controlled, allowing treatments and immunofluorescence in one single chamber selectively. To conclude, we propose the development of two culturing platforms (microstructured well devices and in-flow microfluidic chip), which are the result of separate scientific investigations but have the primary goal of performing treatments in a reproducible manner. Our devices shall improve future studies on drug exposure testing, representing adjustable and versatile cell culture systems.

Automated service provisioning in programmable network infrastructures

Modern networks are undergoing a fast and drastic evolution, with software taking a more predominant role. Virtualization and cloud-like approaches are replacing physical network appliances, reducing the management burden of the operators. Furthermore, networks now expose programmable interfaces for fast and dynamic control over traffic forwarding. This evolution is backed by standard organizations such as ETSI, 3GPP, and IETF. This thesis will describe which are the main trends in this evolution. Then, it will present solutions developed during the three years of Ph.D. to exploit the capabilities these new technologies offer and to study their possible limitations to push further the state-of-the-art. Namely, it will deal with programmable network infrastructure, introducing the concept of Service Function Chaining (SFC) and presenting two possible solutions, one with Openstack and OpenFlow and the other using Segment Routing and IPv6. Then, it will continue with network service provisioning, presenting concepts from Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). These concepts will be applied to network slicing for mission-critical communications and Industrial IoT (IIoT). Finally, it will deal with network abstraction, with a focus on Intent Based Networking (IBN). To summarize, the thesis will include solutions for data plane programming with evaluation on well-known platforms, performance metrics on virtual resource allocations, novel practical application of network slicing on mission-critical communications, an architectural proposal and its implementation for edge technologies in Industrial IoT scenarios, and a formal definition of intent using a category theory approach.

Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems

In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources.

Surveillance risks in IoT applied to smart cities

Nowadays, cities deal with unprecedented pollution and overpopulation problems, and Internet of Things (IoT) technologies are supporting them in facing these issues and becoming increasingly smart. IoT sensors embedded in public infrastructure can provide granular data on the urban environment, and help public authorities to make their cities more sustainable and efficient. Nonetheless, this pervasive data collection also raises high surveillance risks, jeopardizing privacy and data protection rights. Against this backdrop, this thesis addresses how IoT surveillance technologies can be implemented in a legally compliant and ethically acceptable fashion in smart cities. An interdisciplinary approach is embraced to investigate this question, combining doctrinal legal research (on privacy, data protection, criminal procedure) with insights from philosophy, governance, and urban studies. The fundamental normative argument of this work is that surveillance constitutes a necessary feature of modern information societies. Nonetheless, as the complexity of surveillance phenomena increases, there emerges a need to develop more fine-attuned proportionality assessments to ensure a legitimate implementation of monitoring technologies. This research tackles this gap from different perspectives, analyzing the EU data protection legislation and the United States and European case law on privacy expectations and surveillance. Specifically, a coherent multi-factor test assessing privacy expectations in public IoT environments and a surveillance taxonomy are proposed to inform proportionality assessments of surveillance initiatives in smart cities. These insights are also applied to four use cases: facial recognition technologies, drones, environmental policing, and smart nudging. Lastly, the investigation examines competing data governance models in the digital domain and the smart city, reviewing the EU upcoming data governance framework. It is argued that, despite the stated policy goals, the balance of interests may often favor corporate strategies in data sharing, to the detriment of common good uses of data in the urban context.

Hybrid ground-aerial mesh networks for IoT monitoring applications: network design and software platform development

The Internet of Things (IoT) has grown rapidly in recent years, leading to an increased need for efficient and secure communication between connected devices. Wireless Sensor Networks (WSNs) are composed of small, low-power devices that are capable of sensing and exchanging data, and are often used in IoT applications. In addition, Mesh WSNs involve intermediate nodes forwarding data to ensure more robust communication. The integration of Unmanned Aerial Vehicles (UAVs) in Mesh WSNs has emerged as a promising solution for increasing the effectiveness of data collection, as UAVs can act as mobile relays, providing extended communication range and reducing energy consumption. However, the integration of UAVs and Mesh WSNs still poses new challenges, such as the design of efficient control and communication strategies. This thesis explores the networking capabilities of WSNs and investigates how the integration of UAVs can enhance their performance. The research focuses on three main objectives: (1) Ground Wireless Mesh Sensor Networks, (2) Aerial Wireless Mesh Sensor Networks, and (3) Ground/Aerial WMSN integration. For the first objective, we investigate the use of the Bluetooth Mesh standard for IoT monitoring in different environments. The second objective focuses on deploying aerial nodes to maximize data collection effectiveness and QoS of UAV-to-UAV links while maintaining the aerial mesh connectivity. The third objective investigates hybrid WMSN scenarios with air-to-ground communication links. One of the main contribution of the thesis consists in the design and implementation of a software framework called "Uhura", which enables the creation of Hybrid Wireless Mesh Sensor Networks and abstracts and handles multiple M2M communication stacks on both ground and aerial links. The operations of Uhura have been validated through simulations and small-scale testbeds involving ground and aerial devices.

QoS-aware architectures, technologies, and middleware for the cloud continuum

The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions.

Proximity detection protocols for IoT devices

In recent years, we have witnessed the growth of the Internet of Things paradigm, with its increased pervasiveness in our everyday lives. The possible applications are diverse: from a smartwatch able to measure heartbeat and communicate it to the cloud, to the device that triggers an event when we approach an exhibit in a museum. Present in many of these applications is the Proximity Detection task: for instance the heartbeat could be measured only when the wearer is near to a well defined location for medical purposes or the touristic attraction must be triggered only if someone is very close to it. Indeed, the ability of an IoT device to sense the presence of other devices nearby and calculate the distance to them can be considered the cornerstone of various applications, motivating research on this fundamental topic. The energy constraints of the IoT devices are often in contrast with the needs of continuous operations to sense the environment and to achieve high accurate distance measurements from the neighbors, thus making the design of Proximity Detection protocols a challenging task.