19 research outputs found

    Towards large-scale and collaborative spectrum monitoring systems using IoT devices

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    Mención Internacional en el título de doctorThe Electromagnetic (EM) spectrum is well regulated by frequency assignment authorities, national regulatory agencies and the International Communication Union (ITU). Nowadays more and more devices such as mobile phones and Internet-of-Things (IoT) sensors make use of wireless communication. Additionally we need a more efficient use and a better understanding of the EM space to allocate and manage efficiently all communications. Governments and telecommunication operators perform spectrum measurements using expensive and bulky equipments scheduling very specific and limited spectrum campaigns. However, this approach does not scale as it can not allow to widely scan and analyze the spectrum 24/7 in real time due to the high cost of the large deployment. A pervasive deployment of spectrum sensors is required to solve this problem, allowing to monitor and analyze the EM radio waves in real time, across all possible frequencies, and physical locations. This thesis presents ElectroSense, a crowdsourcing and collaborative system that enables large scale deployments using Internet-of-Things (IoT) spectrum sensors to collect EM spectrum data which is analyzed in a big data infrastructure. The ElectroSense platform seeks a more efficient, safe and reliable real-time monitoring of the EM space by improving the accessibility and the democratization of spectrum data for the scientific community, stakeholders and the general public. In this work, we first present the ElectroSense architecture, and the design challenges that must be faced to attract a large community of users and all potential stakeholders. It is envisioned that a large number of sensors deployed in ElectroSense will be at affordable cost, supported by more powerful spectrum sensors when possible. Although low-cost Radio Frequency (RF) sensors have an acceptable performance for measuring the EM spectrum, they present several drawbacks (e.g. frequency range, Analog-to-Digital Converter (ADC), maximum sampling rate, etc.) that can negatively affect the quality of collected spectrum data as well as the applications of interest for the community. In order to counteract the above-mentioned limitations, we propose to exploit the fact that a dense network of spectrum sensors will be in range of the same transmitter(s). We envision to exploit this idea to enable smart collaborative algorithms among IoT RF sensors. In this thesis we identify the main research challenges to enable smart collaborative algorithms among low-cost RF sensors. We explore different crowdsourcing and collaborative scenarios where low-cost spectrum sensors work together in a distributed manner. First, we propose a fast and precise frequency offset estimation method for lowcost spectrum receivers that makes use of Long Term Evolution (LTE) signals broadcasted by the base stations. Second, we propose a novel, fast and precise Time-of-Arrival (ToA) estimation method for aircraft signals using low-cost IoT spectrum sensors that can achieve sub-nanosecond precision. Third, we propose a collaborative time division approach among sensors for sensing the spectrum in order to reduce the network uplink bandwidth for each spectrum sensor. By last, we present a methodology to enable the signal reconstruction in the backend. By multiplexing in frequency a certain number of non-coherent low-cost spectrum sensors, we are able to cover a signal bandwidth that would not otherwise be possible using a single receiver. At the time of writing we are the first looking at the problem of collaborative signal reconstruction and decoding using In-phase & Quadrature (I/Q) data received from low-cost RF sensors. Our results reported in this thesis and obtained from the experiments made in real scenarios, suggest that it is feasible to enable collaborative spectrum monitoring strategies and signal decoding using commodity hardware as RF sensing sensors.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Bozidar Radunovic.- Secretario: Paolo Casari.- Vocal: Fco. Javier Escribano Aparici

    Datenerfassung und Privatsphäre in partizipativen Sensornetzen

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    Partizipative Sensornetze (PSNs) stellen eine neue Art von Sensornetzen dar, die auf Basis von freiwillig zur Verfügung gestellten Mobiltelefonen etabliert werden. Sie ermöglichen eine großflächige Erfassung von Messdaten im direkten Umfeld von Menschen und können für zahlreiche Anwendungsszenarien verwendet werden. Neben ihren Vorzügen bringen PSNs aber auch Schwierigkeiten mit sich. Zwei zentrale Herausforderungen sind die ressourcenschonende Datenerfassung und der Schutz der Privatsphäre – beide resultieren aus der Instrumentalisierung privater Mobiltelefone zur Datenerfassung. Da der primäre Verwendungszweck der Geräte nicht die Aufzeichnung von Messdaten ist, darf diese deren Ressourcen nicht merklich belasten. Außerdem muss sichergestellt werden, dass durch die Erfassung von Messdaten die Privatsphäre der teilnehmenden Nutzer nicht verletzt wird. Der erste Teil der Arbeit beschäftigt sich mit dem Aspekt der ressourcenschonenden Datenerfassung. Zunächst werden PSNs betrachtet, bei denen punktuell Messungen durchgeführt werden. Bei diesen Netzen müssen die teilnehmenden Geräte über die durchzuführenden Messungen unterrichtet werden. Damit hierbei die Ressourcen der Endgeräte nicht unnötig belastet werden, wird ein Konzept vorgestellt, das einerseits eine robuste Verteilung der Messaufgaben sicherstellt, gleichzeitig jedoch versucht, die Energieressourcen der Mobiltelefone zu schonen. Bei PSNs mit großflächiger und kontinuierlicher Datenerfassung spielt die Verteilung der Messaufgaben keine so entscheidende Rolle. Hier muss vielmehr sichergestellt werden, dass die Energie- und die Übertragungskosten auf Seiten der Nutzer möglichst gering bleiben. Aus diesem Grund wird ein Ansatz zur lokalen Gruppierung von Messknoten beschrieben, der durch eine Aufteilung der anfallenden Aufgaben und eine intelligente Auswahl der Knoten zu einer ressourcenschonenden und weniger redundanten Datenerfassung führt. Der zweite Teil der Arbeit befasst sich mit dem Schutz der Privatsphäre der Teilnehmer und beinhaltet zwei Themenblöcke. Zum einen wird ein Ansatz zur automatisierten Erzeugung von Privatsphäre-Zonen vorgestellt, der ohne das Eingreifen der Nutzer die Zonen an das jeweilige Umfeld anpasst. Diese Zonen werden um die vom Nutzer häufig besuchten Orte erstellt und verhindern so mögliche, auf der Identifikation dieser Orte basierende Deanonymisierungsangriffe. Zum anderen wird ein Kalibrierungssystem für PSNs beschrieben, dessen Fokus sowohl auf der Verbesserung der Datenqualität als auch auf der Wahrung der Privatsphäre der Nutzer liegt. Hierfür ermöglicht dieses eine rückwirkende Anpassung bereits übertragener Daten, verhindert aber gleichzeitig durch eine Modifikation der Kalibrierungsparameter und der Upload-Zeitpunkte eine direkte Zuordnung zu einem Nutzer.Participatory Sensing Networks (PSNs) represent a new kind of sensor networks that are established on the basis of voluntarily provided mobile phones. They allow for large-scale data collection in the immediate environment of people and can be used for various application scenarios. However, alongside their advantages, PSNs entail several difficulties. Two key challenges are the resource-efficient data collection and the protection of privacy - both resulting from exploiting private mobile phones for data collection. As the recording of measurement data is not the devices’ primary purpose, it must not significantly burden their resources. In addition, it has to be ensured that the privacy of participating users is not violated by the acquisition of measurement data. The first part of this thesis addresses the issue of resource-efficient data collection. At first, PSNs are examined in which measurements are only conducted at selected places. In these networks, the participating devices have to be informed about the required measurements. To avoid an unnecessary burdening of device resources at this stage, a concept is presented that ensures a robust distribution of measurement tasks and, at the same time, tries to conserve the mobile phones’ energy resources. In PSNs with large and continuous data collection, the distribution of measurement tasks is less essential. It is rather necessary to ensure that energy and transmission costs on the user side remain as low as possible. For this reason, an approach for the local clustering of measurement nodes is described that allows for a resource-efficient and less redundant data collection by dividing and intelligently assigning occurring tasks. The second part of the thesis deals with the protection of the participants’ privacy and contains two thematic blocks. Firstly, an approach to automate the generation of privacy zones is presented. It adjusts the zones to the environment without the intervention of the user. These zones are created around the user’s frequently visited places and thereby prevent deanonymisation attacks based on the identification of these places. Secondly, a calibration system for PSNs is described that focuses both on improving data quality and on the protection of user privacy. It allows for a retroactive adjustment of already transferred data, but simultaneously prevents an unambiguous attribution to a user by modifying the calibration parameters and the time of their transmission

    Datenerfassung und Privatsphäre in partizipativen Sensornetzen

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    Partizipative Sensornetze (PSNs) stellen eine neue Art von Sensornetzen dar, die auf Basis von freiwillig zur Verfügung gestellten Mobiltelefonen etabliert werden. Sie ermöglichen eine großflächige Erfassung von Messdaten im direkten Umfeld von Menschen und können für zahlreiche Anwendungsszenarien verwendet werden. Neben ihren Vorzügen bringen PSNs aber auch Schwierigkeiten mit sich. Zwei zentrale Herausforderungen sind die ressourcenschonende Datenerfassung und der Schutz der Privatsphäre – beide resultieren aus der Instrumentalisierung privater Mobiltelefone zur Datenerfassung. Da der primäre Verwendungszweck der Geräte nicht die Aufzeichnung von Messdaten ist, darf diese deren Ressourcen nicht merklich belasten. Außerdem muss sichergestellt werden, dass durch die Erfassung von Messdaten die Privatsphäre der teilnehmenden Nutzer nicht verletzt wird. Der erste Teil der Arbeit beschäftigt sich mit dem Aspekt der ressourcenschonenden Datenerfassung. Zunächst werden PSNs betrachtet, bei denen punktuell Messungen durchgeführt werden. Bei diesen Netzen müssen die teilnehmenden Geräte über die durchzuführenden Messungen unterrichtet werden. Damit hierbei die Ressourcen der Endgeräte nicht unnötig belastet werden, wird ein Konzept vorgestellt, das einerseits eine robuste Verteilung der Messaufgaben sicherstellt, gleichzeitig jedoch versucht, die Energieressourcen der Mobiltelefone zu schonen. Bei PSNs mit großflächiger und kontinuierlicher Datenerfassung spielt die Verteilung der Messaufgaben keine so entscheidende Rolle. Hier muss vielmehr sichergestellt werden, dass die Energie- und die Übertragungskosten auf Seiten der Nutzer möglichst gering bleiben. Aus diesem Grund wird ein Ansatz zur lokalen Gruppierung von Messknoten beschrieben, der durch eine Aufteilung der anfallenden Aufgaben und eine intelligente Auswahl der Knoten zu einer ressourcenschonenden und weniger redundanten Datenerfassung führt. Der zweite Teil der Arbeit befasst sich mit dem Schutz der Privatsphäre der Teilnehmer und beinhaltet zwei Themenblöcke. Zum einen wird ein Ansatz zur automatisierten Erzeugung von Privatsphäre-Zonen vorgestellt, der ohne das Eingreifen der Nutzer die Zonen an das jeweilige Umfeld anpasst. Diese Zonen werden um die vom Nutzer häufig besuchten Orte erstellt und verhindern so mögliche, auf der Identifikation dieser Orte basierende Deanonymisierungsangriffe. Zum anderen wird ein Kalibrierungssystem für PSNs beschrieben, dessen Fokus sowohl auf der Verbesserung der Datenqualität als auch auf der Wahrung der Privatsphäre der Nutzer liegt. Hierfür ermöglicht dieses eine rückwirkende Anpassung bereits übertragener Daten, verhindert aber gleichzeitig durch eine Modifikation der Kalibrierungsparameter und der Upload-Zeitpunkte eine direkte Zuordnung zu einem Nutzer.Participatory Sensing Networks (PSNs) represent a new kind of sensor networks that are established on the basis of voluntarily provided mobile phones. They allow for large-scale data collection in the immediate environment of people and can be used for various application scenarios. However, alongside their advantages, PSNs entail several difficulties. Two key challenges are the resource-efficient data collection and the protection of privacy - both resulting from exploiting private mobile phones for data collection. As the recording of measurement data is not the devices’ primary purpose, it must not significantly burden their resources. In addition, it has to be ensured that the privacy of participating users is not violated by the acquisition of measurement data. The first part of this thesis addresses the issue of resource-efficient data collection. At first, PSNs are examined in which measurements are only conducted at selected places. In these networks, the participating devices have to be informed about the required measurements. To avoid an unnecessary burdening of device resources at this stage, a concept is presented that ensures a robust distribution of measurement tasks and, at the same time, tries to conserve the mobile phones’ energy resources. In PSNs with large and continuous data collection, the distribution of measurement tasks is less essential. It is rather necessary to ensure that energy and transmission costs on the user side remain as low as possible. For this reason, an approach for the local clustering of measurement nodes is described that allows for a resource-efficient and less redundant data collection by dividing and intelligently assigning occurring tasks. The second part of the thesis deals with the protection of the participants’ privacy and contains two thematic blocks. Firstly, an approach to automate the generation of privacy zones is presented. It adjusts the zones to the environment without the intervention of the user. These zones are created around the user’s frequently visited places and thereby prevent deanonymisation attacks based on the identification of these places. Secondly, a calibration system for PSNs is described that focuses both on improving data quality and on the protection of user privacy. It allows for a retroactive adjustment of already transferred data, but simultaneously prevents an unambiguous attribution to a user by modifying the calibration parameters and the time of their transmission

    Human-in-the-Loop Cyber-Physical-Systems based on Smartphones

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    Tese de doutoramento em Ciências e Tecnologias da Informação, apresentada ao Departamento de Engenharia Informática da Faculdade de Ciências e Tecnologia da Universidade de CoimbraTechnological devices increasingly become smaller, more mobile, powerful and efficient. However, each time we have to hurdle through unintuitive menus, errors and incompatibilities we become stressed by our technology. As first put forward by the renowned computer scientist Mark Weiser, the ultimate form of computers may be an extension of our subconscious. The ideal computer would be capable of truly understanding people's unconscious actions and desires. Instead of humans adapting to technology and learning how to use it, it would be technology that would adapt to the disposition and uniqueness of each human being. This thesis focuses on the realm of Human-in-the-loop Cyber-Physical Systems (HiTLCPSs). HiTLCPSs infer the users’ intents, psychological states, emotions and actions, using this information to determine the system's behavior. This involves using a large variety of sensors and mobile devices to monitor and evaluate human nature. Therefore, this technology has strong ties with wireless sensor networks, robotics, machine-learning and the Internet of Things. In particular, our work focuses on the usage of smartphones within these systems. It begins by describing a framework to understand the principles and theory of HiTLCPSs. It provides some insights into current research being done on this topic, its challenges, and requirements. Another of the thesis' objectives is to present our innovative taxonomy of human roles, where we attempt to understand how a human may interact with HiTLCPSs and how to best explore this resource. This thesis also describes concrete examples of the practical usage of HiTL paradigms. As such, we included a comprehensive description of our research work and associated prototypes, where the major theoretical concepts behind HiTLCPS were applied and evaluated to specific scenarios. Finally, we discuss our personal view on the future and evolution of these systems.A tecnologia tem vindo a tornar-se cada vez mais pequena, móvel, poderosa e eficiente. No entanto, lidar com menus pouco intuitivos, erros, e incompatibilidades, causa frustração aos seus utilizadores. Segundo o reconhecido cientista Mark Weiser, os computadores do futuro poderão vir a existir como se fossem uma extensão do nosso subconsciente. O computador ideal seria capaz de entender, em toda a sua plenitude, as ações e os desejos inconscientes dos seres humanos. Em vez de serem os humanos a adaptarem-se à tecnologia e a aprender a usá-la, seria a tecnologia a aprender a adaptar-se à disposição e individualidade de cada ser humano. Esta tese foca-se na área dos Human-in-the-loop Cyber-Physical Systems (HiTLCPSs). Os HiTLCPSs inferem as intenções, estados psicológicos, emoções e ações dos seus utilizadores, usando esta informação para determinar o comportamento do sistema ciber-físico. Isto envolve a utilização de uma grande variedade de sensores e dispositivos móveis que monitorizam e avaliam a natureza humana. Assim sendo, esta tecnologia tem fortes ligações com redes de sensores sem fios, robótica, algoritmos de aprendizagem de máquina e a Internet das Coisas. Em particular, o nosso trabalho focou-se na utilização de smartphones dentro destes sistemas. Começamos por descrever uma estrutura para compreender os princípios e teoria associados aos HiTLCPSs. Esta análise permitiu-nos adquirir alguma clareza sobre a investigação a ser feita sobre este tópico, e sobre os seus desafios e requisitos. Outro dos objetivos desta tese é o de apresentar a nossa inovadora taxonomia sobre os papeis do ser humano nos HiTLCPSs, onde tentamos perceber as possíveis interações do ser humano com estes sistemas e as melhores formas de explorar este recurso. Esta tese também descreve exemplos concretos da utilização prática dos paradigmas HiTL. Desta forma, incluímos uma descrição do nosso trabalho experimental e dos protótipos que lhe estão associados, onde os conceitos teóricos dos HiTLCPSs foram aplicados e avaliados em diversos casos de estudo. Por fim, apresentamos a nossa perspetiva pessoal sobre o futuro e evolução destes sistemas.Fundação Luso-Americana para o DesenvolvimentoFP7-ICT-2007-2 GINSENG projectiCIS project (CENTRO-07-ST24-FEDER-002003)SOCIALITE project (PTDC/EEI-SCR/2072/2014

    Routing for Wireless Sensor Networks: From Collection to Event-Triggered Applications

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    Wireless Sensor Networks (WSNs) are collections of sensing devices using wireless communication to exchange data. In the past decades, steep advancements in the areas of microelectronics and communication systems have driven an explosive growth in the deployment of WSNs. Novel WSN applications have penetrated multiple areas, from monitoring the structural stability of historic buildings, to tracking animals in order to understand their behavior, or monitoring humans' health. The need to convey data from increasingly complex applications in a reliable and cost-effective manner translates into stringent performance requirements for the underlying WSNs. In the frame of this thesis, we have focused on developing routing protocols for multi-hop WSNs, that significantly improve their reliability, energy consumption and latency. Acknowledging the need for application-specific trade-offs, we have split our contribution into two parts. Part 1 focuses on collection protocols, catering to applications with high reliability and energy efficiency constraints, while the protocols developed in part 2 are subject to an additional bounded latency constraint. The two mechanisms introduced in the first part, WiseNE and Rep, enable the use of composite metrics, and thus significantly improve the link estimation accuracy and transmission reliability, at an energy expense far lower than the one achieved in previous proposals. The novel beaconing scheme WiseNE enables the energy-efficient addition of the RSSI (Received Signal Strength Indication) and LQI (Link Quality Indication) metrics to the link quality estimate by decoupling the sampling and exploration periods of each mote. This decoupling allows the use of the Trickle Algorithm, a key driver of protocols' energy efficiency, in conjunction with composite metrics. WiseNE has been applied to the Triangle Metric and validated in an online deployment. The section continues by introducing Rep, a novel sampling mechanism that leverages the packet repetitions already present in low-power preamble-sampling MAC protocols in order to improve the WSN energy consumption by one order of magnitude. WiseNE, Rep and the novel PRSSI (Penalized RSSI, a combination of PRR and RSSI) composite metric have been validated in a real smart city deployment. Part 2 introduces two mechanisms that were developed in the frame of the WiseSkin project (an initiative aimed at designing highly sensitive artificial skin for human limb prostheses), and are generally applicable to the domain of cyber-physical systems. It starts with Glossy-W, a protocol that leverages the superior energy-latency trade-off of flooding schemes based on concurrent transmissions. Glossy-W ensures the stringent synchronization requirements necessary for robust flooding, irrespective of the number of motes simultaneously reporting an event. Part 2 also introduces SCS (Synchronized Channel Sampling), a novel mechanism capable of reducing the power required for periodic polling, while maintaining the event detection reliability, and enhancing the network coexistence. The testbed experiments performed show that SCS manages to reduce the energy consumption of the state-of-the-art protocol Back-to-Back Robust Flooding by over one third, while maintaining an equivalent reliability, and remaining compatible with simultaneous event detection. SCS' benefits can be extended to the entire family of state-of-the-art protocols relying on concurrent transmissions

    IoT and Sensor Networks in Industry and Society

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    The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

    Modelado de transmisión eficiente de datos para eventos multivariantes basados en umbral

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    This doctoral thesis delves into the optimization of communications in sensor networks for a specific purpose: to evaluate threshold-based events that depend on multiple distributed variables. This motivation is behind the detailed research presented here in the form of a compendium of papers. The developed work is structured in 3 scientific contributions in articles. Out of those 3 contributions, the most theoretical work has been described in 2 of them, leaving the third article for the presentation of a methodological support tool with great scientific impact and relevance in this doctoral thesis. Due to the two theoretical and large–scale contributions in the proposed field, a solution is proposed which is stated as an hypotheses. The first contribution is the mathematical foundations for modelling data reduction in the sensor network and measuring its influence on the quality of the event evaluation. For this purpose, a set of functions and parameters is defined. This logic modifies the cardinality of the mathematical domains in which information is defined in order to save traffic. Specific metrics that consider the time delays in the state changes of the evaluated condition are also defined. The second contribution is an adaptive algorithm that, taking into account the logical context of the system information, parameterizes the proposed model at runtime. As a result, this technique maximizes traffic reduction and minimizes error in the evaluation of the event simultaneously, obtaining promising results. As a methodological contribution, a procedure for generating pseudo-realistic random signals is also described, a useful tool for easily obtaining large datasets suitable for experimentation, which has been applied in the described contributions.Esta tesis doctoral profundiza en la optimización de las comunicaciones en redes de sensores con un propósito específico: evaluar eventos basados en umbral que dependen de múltiples variables distribuidas. Con esta motivación se desarrolla la investigación detallada aquí en forma compendio de artículos. El trabajo desarrollado se estructura en 3 aportaciones científicas en artículos. De esas 3 aportaciones, el trabajo en su vertiente más teórica se desarrolla en 2 de ellas, quedando el tercer artículo para la presentación de una herramienta de soporte metodológico con gran impacto científico y de relevancia en esta tesis doctoral. Gracias a las dos aportaciones teóricas y de gran calado en el ámbito propuesto se propone una solución que se plantea en forma de hipótesis. La primera aportación son los fundamentos matemáticos para modelar la reducción de datos en la red de sensores y medir su incidencia en la calidad de la evaluación del evento. Para ello define una serie de funciones y parámetros que alteran la cardinalidad de los dominios matemáticos en los que se define la información, así como métricas específicas que tienen en cuenta los desfases temporales en los cambios de estado de la condición evaluada. La segunda aportación es un algoritmo adaptativo que, considerando el contexto lógico de la información del sistema, parametriza el modelo propuesto en tiempo de ejecución. Como resultado, esta técnica maximiza la reducción de tráfico y minimiza el error en la evaluación del evento simultáneamente, obteniendo resultados prometedores. Como tercera aportación se describe también un procedimiento para generar señales aleatorias pseudo–realistas, una herramienta útil para disponer fácilmente de grandes conjuntos de datos adecuados para experimentación, que ha sido utilizada en las aportaciones descritas

    Sensors and Systems for Indoor Positioning

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    This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

    Solutions for large scale, efficient, and secure Internet of Things

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    The design of a general architecture for the Internet of Things (IoT) is a complex task, due to the heterogeneity of devices, communication technologies, and applications that are part of such systems. Therefore, there are significant opportunities to improve the state of the art, whether to better the performance of the system, or to solve actual issues in current systems. This thesis focuses, in particular, on three aspects of the IoT. First, issues of cyber-physical systems are analysed. In these systems, IoT technologies are widely used to monitor, control, and act on physical entities. One of the most important issue in these scenarios are related to the communication layer, which must be characterized by high reliability, low latency, and high energy efficiency. Some solutions for the channel access scheme of such systems are proposed, each tailored to different specific scenarios. These solutions, which exploit the capabilities of state of the art radio transceivers, prove effective in improving the performance of the considered systems. Positioning services for cyber-physical systems are also investigated, in order to improve the accuracy of such services. Next, the focus moves to network and service optimization for traffic intensive applications, such as video streaming. This type of traffic is common amongst non-constrained devices, like smartphones and augmented/virtual reality headsets, which form an integral part of the IoT ecosystem. The proposed solutions are able to increase the video Quality of Experience while wasting less bandwidth than state of the art strategies. Finally, the security of IoT systems is investigated. While often overlooked, this aspect is fundamental to enable the ubiquitous deployment of IoT. Therefore, security issues of commonly used IoT protocols are presented, together with a proposal for an authentication mechanism based on physical channel features. This authentication strategy proved to be effective as a standalone mechanism or as an additional security layer to improve the security level of legacy systems

    ESARDA 37th Annual Meeting Proceedings

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    The 37th ESARDA symposium on Safeguards and Nuclear Non-Proliferation was held in Manchester, United Kingdom from 19-21 May, 2015. The Symposium has been preceded by meetings of the ESARDA Working Groups on 18 May 2015. The event has once again been an opportunity for research organisations, safeguards authorities and nuclear plant operators to exchange information on new aspects of international safeguards and non-proliferation, as well as recent developments in nuclear safeguards and non-proliferation related research activities and their implications for the safeguards community. The Proceedings contains the papers (118) submitted according to deadlines.JRC.E.8-Nuclear securit
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