957 resultados para swd: Ubiquitous Computing


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Il proliferare di dispositivi di elaborazione e comunicazione mobili (telefoni cellulari, computer portatili, PDA, wearable devices, personal digital assistant) sta guidando un cambiamento rivoluzionario nella nostra società dell'informazione. Si sta migrando dall'era dei Personal Computer all'era dell'Ubiquitous Computing, in cui un utente utilizza, parallelamente, svariati dispositivi elettronici attraverso cui può accedere a tutte le informazioni, ovunque e quantunque queste gli si rivelino necessarie. In questo scenario, anche le mappe digitali stanno diventando sempre più parte delle nostre attività quotidiane; esse trasmettono informazioni vitali per una pletora di applicazioni che acquistano maggior valore grazie alla localizzazione, come Yelp, Flickr, Facebook, Google Maps o semplicemente le ricerche web geo-localizzate. Gli utenti di PDA e Smartphone dipendono sempre più dai GPS e dai Location Based Services (LBS) per la navigazione, sia automobilistica che a piedi. Gli stessi servizi di mappe stanno inoltre evolvendo la loro natura da uni-direzionale a bi-direzionale; la topologia stradale è arricchita da informazioni dinamiche, come traffico in tempo reale e contenuti creati dagli utenti. Le mappe digitali aggiornabili dinamicamente sono sul punto di diventare un saldo trampolino di lancio per i sistemi mobili ad alta dinamicità ed interattività, che poggiando su poche informazioni fornite dagli utenti, porteranno una moltitudine di applicazioni innovative ad un'enorme base di consumatori. I futuri sistemi di navigazione per esempio, potranno utilizzare informazioni estese su semafori, presenza di stop ed informazioni sul traffico per effettuare una ottimizzazione del percorso che valuti simultaneamente fattori come l'impronta al carbonio rilasciata, il tempo di viaggio effettivamente necessario e l'impatto della scelta sul traffico locale. In questo progetto si mostra come i dati GPS raccolti da dispositivi fissi e mobili possano essere usati per estendere le mappe digitali con la locazione dei segnali di stop, dei semafori e delle relative temporizzazioni. Queste informazioni sono infatti oggi rare e locali ad ogni singola municipalità, il che ne rende praticamente impossibile il pieno reperimento. Si presenta quindi un algoritmo che estrae utili informazioni topologiche da agglomerati di tracciati gps, mostrando inoltre che anche un esiguo numero di veicoli equipaggiati con la strumentazione necessaria sono sufficienti per abilitare l'estensione delle mappe digitali con nuovi attributi. Infine, si mostrerà come l'algoritmo sia in grado di lavorare anche con dati mancanti, ottenendo ottimi risultati e mostrandosi flessibile ed adatto all'integrazione in sistemi reali.

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Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

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Nowadays, in Ubiquitous computing scenarios users more and more require to exploit online contents and services by means of any device at hand, no matter their physical location, and by personalizing and tailoring content and service access to their own requirements. The coordinated provisioning of content tailored to user context and preferences, and the support for mobile multimodal and multichannel interactions are of paramount importance in providing users with a truly effective Ubiquitous support. However, so far the intrinsic heterogeneity and the lack of an integrated approach led to several either too vertical, or practically unusable proposals, thus resulting in poor and non-versatile support platforms for Ubiquitous computing. This work investigates and promotes design principles to help cope with these ever-changing and inherently dynamic scenarios. By following the outlined principles, we have designed and implemented a middleware support platform to support the provisioning of Ubiquitous mobile services and contents. To prove the viability of our approach, we have realized and stressed on top of our support platform a number of different, extremely complex and heterogeneous content and service provisioning scenarios. The encouraging results obtained are pushing our research work further, in order to provide a dynamic platform that is able to not only dynamically support novel Ubiquitous applicative scenarios by tailoring extremely diverse services and contents to heterogeneous user needs, but is also able to reconfigure and adapt itself in order to provide a truly optimized and tailored support for Ubiquitous service provisioning.

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The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

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"I computer del nuovo millennio saranno sempre più invisibili, o meglio embedded, incorporati agli oggetti, ai mobili, anche al nostro corpo. L'intelligenza elettronica sviluppata su silicio diventerà sempre più diffusa e ubiqua. Sarà come un'orchestra di oggetti interattivi, non invasivi e dalla presenza discreta, ovunque". [Mark Weiser, 1991] La visione dell'ubiquitous computing, prevista da Weiser, è ormai molto vicina alla realtà e anticipa una rivoluzione tecnologica nella quale l'elaborazione di dati ha assunto un ruolo sempre più dominante nella nostra vita quotidiana. La rivoluzione porta non solo a vedere l'elaborazione di dati come un'operazione che si può compiere attraverso un computer desktop, legato quindi ad una postazione fissa, ma soprattutto a considerare l'uso della tecnologia come qualcosa di necessario in ogni occasione, in ogni luogo e la diffusione della miniaturizzazione dei dispositivi elettronici e delle tecnologie di comunicazione wireless ha contribuito notevolmente alla realizzazione di questo scenario. La possibilità di avere a disposizione nei luoghi più impensabili sistemi elettronici di piccole dimensioni e autoalimentati ha contribuito allo sviluppo di nuove applicazioni, tra le quali troviamo le WSN (Wireless Sensor Network), ovvero reti formate da dispositivi in grado di monitorare qualsiasi grandezza naturale misurabile e inviare i dati verso sistemi in grado di elaborare e immagazzinare le informazioni raccolte. La novità introdotta dalle reti WSN è rappresentata dalla possibilità di effettuare monitoraggi con continuità delle più diverse grandezze fisiche, il che ha consentito a questa nuova tecnologia l'accesso ad un mercato che prevede una vastità di scenari indefinita. Osservazioni estese sia nello spazio che nel tempo possono essere inoltre utili per poter ricavare informazioni sull'andamento di fenomeni naturali che, se monitorati saltuariamente, non fornirebbero alcuna informazione interessante. Tra i casi d'interesse più rilevanti si possono evidenziare: - segnalazione di emergenze (terremoti, inondazioni) - monitoraggio di parametri difficilmente accessibili all'uomo (frane, ghiacciai) - smart cities (analisi e controllo di illuminazione pubblica, traffico, inquinamento, contatori gas e luce) - monitoraggio di parametri utili al miglioramento di attività produttive (agricoltura intelligente, monitoraggio consumi) - sorveglianza (controllo accessi ad aree riservate, rilevamento della presenza dell'uomo) Il vantaggio rappresentato da un basso consumo energetico, e di conseguenza un tempo di vita della rete elevato, ha come controparte il non elevato range di copertura wireless, valutato nell'ordine delle decine di metri secondo lo standard IEEE 802.15.4. Il monitoraggio di un'area di grandi dimensioni richiede quindi la disposizione di nodi intermedi aventi le funzioni di un router, il cui compito sarà quello di inoltrare i dati ricevuti verso il coordinatore della rete. Il tempo di vita dei nodi intermedi è di notevole importanza perché, in caso di spegnimento, parte delle informazioni raccolte non raggiungerebbero il coordinatore e quindi non verrebbero immagazzinate e analizzate dall'uomo o dai sistemi di controllo. Lo scopo di questa trattazione è la creazione di un protocollo di comunicazione che preveda meccanismi di routing orientati alla ricerca del massimo tempo di vita della rete. Nel capitolo 1 vengono introdotte le WSN descrivendo caratteristiche generali, applicazioni, struttura della rete e architettura hardware richiesta. Nel capitolo 2 viene illustrato l'ambiente di sviluppo del progetto, analizzando le piattaforme hardware, firmware e software sulle quali ci appoggeremo per realizzare il progetto. Verranno descritti anche alcuni strumenti utili per effettuare la programmazione e il debug della rete. Nel capitolo 3 si descrivono i requisiti di progetto e si realizza una mappatura dell'architettura finale. Nel capitolo 4 si sviluppa il protocollo di routing, analizzando i consumi e motivando le scelte progettuali. Nel capitolo 5 vengono presentate le interfacce grafiche utilizzate utili per l'analisi dei dati. Nel capitolo 6 vengono esposti i risultati sperimentali dell'implementazione fissando come obiettivo il massimo lifetime della rete.

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Negli ultimi anni si è imposto il concetto di Ubiquitous Computing, ovvero la possibilità di accedere al web e di usare applicazioni per divertimento o lavoro in qualsiasi momento e in qualsiasi luogo. Questo fenomeno sta cambiando notevolmente le abitudini delle persone e ciò è testimoniato anche dal fatto che il mercato mobile è in forte ascesa: da fine 2014 sono 45 milioni gli smartphone e 12 milioni i tablet in circolazione in Italia. Sembra quasi impossibile, dunque, rinunciare al mobile, soprattutto per le aziende: il nuovo modo di comunicare ha reso necessaria l’introduzione del Mobile Marketing e per raggiungere i propri clienti ora uno degli strumenti più efficaci e diretti sono le applicazioni. Esse si definiscono native se si pongono come traguardo un determinato smartphone e possono funzionare solo per quel sistema operativo. Infatti un’app costruita, per esempio, per Android non può funzionare su dispositivi Apple o Windows Phone a meno che non si ricorra al processo di porting. Ultimamente però è richiesto un numero sempre maggiore di app per piattaforma e i dispositivi presenti attualmente sul mercato presentano differenze tra le CPU, le interfacce (Application Programming Interface), i sistemi operativi, l’hardware, etc. Nasce quindi la necessità di creare applicazioni che possano funzionare su più sistemi operativi, ovvero le applicazioni platform-independent. Per facilitare e supportare questo genere di lavoro sono stati definiti nuovi ambienti di sviluppo tra i quali Sencha Touch e Apache Cordova. Il risultato finale dello sviluppo di un’app attraverso questi framework è proprio quello di ottenere un oggetto che possa essere eseguito su qualsiasi dispositivo. Naturalmente la resa non sarà la stessa di un’app nativa, la quale ha libero accesso a tutte le funzionalità del dispositivo (rubrica, messaggi, notifiche, geolocalizzazione, fotocamera, accelerometro, etc.), però con questa nuova app vi è la garanzia di un costo di sviluppo minore e di una richiesta considerevole sul mercato. L’obiettivo della tesi è quello di analizzare questo scenario attraverso un caso di studio proveniente da una realtà aziendale che presenta proprio la necessità di sviluppare un’applicazione per più piattaforme. Nella prima parte della tesi viene affrontata la tematica del mobile computing e quella del dualismo tra la programmazione nativa e le web app: verranno analizzate le caratteristiche delle due diverse tipologie cercando di capire quale delle due risulti essere la migliore. Nella seconda parte sarà data luce a uno dei più importanti framework per la costruzione di app multi-piattaforma: Sencha Touch. Ne verranno analizzate le caratteristiche, soffermandosi in particolare sul pattern MVC e si potrà vedere un confronto con altri framework. Nella terza parte si tratterà il caso di studio, un app mobile per Retail basata su Sencha Touch e Apache Cordova. Nella parte finale si troveranno alcune riflessioni e conclusioni sul mobile platform-independent e sui vantaggi e gli svantaggi dell’utilizzo di JavaScript per sviluppare app.

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In den letzten Jahren wurde die Vision einer Welt smarter Alltagsgegenstände unter den Begriffen wie Ubiquitous Computing, Pervasive Computing und Ambient Intelligence in der Öffentlichkeit wahrgenommen. Die smarten Gegenstände sollen mit digitaler Logik, Sensorik und der Möglichkeit zur Vernetzung ausgestattet werden. Somit bilden sie ein „Internet der Dinge“, in dem der Computer als eigenständiges Gerät verschwindet und in den Objekten der physischen Welt aufgeht. Während auf der einen Seite die Vision des „Internet der Dinge“ durch die weiter anhaltenden Fortschritte in der Informatik, Mikroelektronik, Kommunikationstechnik und Materialwissenschaft zumindest aus technischer Sicht wahrscheinlich mittelfristig realisiert werden kann, müssen auf der anderen Seite die damit zusammenhängenden ökonomischen, rechtlichen und sozialen Fragen geklärt werden. Zur Weiterentwicklung und Realisierung der Vision des „Internet der Dinge“ wurde erstmals vom AutoID-Center das EPC-Konzept entwickelt, welches auf globale netzbasierte Informationsstandards setzt und heute von EPCglobal weiterentwickelt und umgesetzt wird. Der EPC erlaubt es, umfassende Produktinformationen über das Internet zur Verfügung zu stellen. Die RFID-Technologie stellt dabei die wichtigste Grundlage des „Internet der Dinge“ dar, da sie die Brücke zwischen der physischen Welt der Produkte und der virtuellen Welt der digitalen Daten schlägt. Die Objekte, die mit RFID-Transpondern ausgestattet sind, können miteinander kommunizieren und beispielsweise ihren Weg durch die Prozesskette finden. So können sie dann mit Hilfe der auf den RFID-Transpondern gespeicherten Informationen Förderanlagen oder sonstige Maschinen ohne menschliches Eingreifen selbstständig steuern.

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Mobile learning, in the past defined as learning with mobile devices, now refers to any type of learning-on-the-go or learning that takes advantage of mobile technologies. This new definition shifted its focus from the mobility of technology to the mobility of the learner (O'Malley and Stanton 2002; Sharples, Arnedillo-Sanchez et al. 2009). Placing emphasis on the mobile learner’s perspective requires studying “how the mobility of learners augmented by personal and public technology can contribute to the process of gaining new knowledge, skills, and experience” (Sharples, Arnedillo-Sanchez et al. 2009). The demands of an increasingly knowledge based society and the advances in mobile phone technology are combining to spur the growth of mobile learning. Around the world, mobile learning is predicted to be the future of online learning, and is slowly entering the mainstream education. However, for mobile learning to attain its full potential, it is essential to develop more advanced technologies that are tailored to the needs of this new learning environment. A research field that allows putting the development of such technologies onto a solid basis is user experience design, which addresses how to improve usability and therefore user acceptance of a system. Although there is no consensus definition of user experience, simply stated it focuses on how a person feels about using a product, system or service. It is generally agreed that user experience adds subjective attributes and social aspects to a space that has previously concerned itself mainly with ease-of-use. In addition, it can include users’ perceptions of usability and system efficiency. Recent advances in mobile and ubiquitous computing technologies further underline the importance of human-computer interaction and user experience (feelings, motivations, and values) with a system. Today, there are plenty of reports on the limitations of mobile technologies for learning (e.g., small screen size, slow connection), but there is a lack of research on user experience with mobile technologies. This dissertation will fill in this gap by a new approach in building a user experience-based mobile learning environment. The optimized user experience we suggest integrates three priorities, namely a) content, by improving the quality of delivered learning materials, b) the teaching and learning process, by enabling live and synchronous learning, and c) the learners themselves, by enabling a timely detection of their emotional state during mobile learning. In detail, the contributions of this thesis are as follows: • A video codec optimized for screencast videos which achieves an unprecedented compression rate while maintaining a very high video quality, and a novel UI layout for video lectures, which together enable truly mobile access to live lectures. • A new approach in HTTP-based multimedia delivery that exploits the characteristics of live lectures in a mobile context and enables a significantly improved user experience for mobile live lectures. • A non-invasive affective learning model based on multi-modal emotion detection with very high recognition rates, which enables real-time emotion detection and subsequent adaption of the learning environment on mobile devices. The technology resulting from the research presented in this thesis is in daily use at the School of Continuing Education of Shanghai Jiaotong University (SOCE), a blended-learning institution with 35.000 students.

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Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

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Este trabajo consiste en la elaboración de un proyecto de investigación, orientado al estudio del Internet de las Cosas y los riesgos que presenta para la privacidad. En los últimos años se han puesto en marcha numerosos proyectos y se han realizado grandes avances tecnológicos con el fin de hacer del Internet de las Cosas una realidad, sin embargo aspectos críticos como la seguridad y la privacidad todavía no están completamente solucionados. El objetivo de este Trabajo Fin de Master es realizar un análisis en profundidad del Internet del Futuro, ampliando los conocimientos adquiridos durante el Máster, estudiando paso a paso los fundamentos sobre los que se asienta y reflexionando acerca de los retos a los que se enfrenta y el efecto que puede tener su implantación para la privacidad. El trabajo se compone de 14 capítulos estructurados en 4 partes. Una primera parte de introducción en la que se explican los conceptos del Internet de las Cosas y la computación ubicua, como preámbulo a las siguientes secciones. Posteriormente, en la segunda parte, se analizan los aspectos tecnológicos y relativos a la estandarización de esta nueva red. En la tercera parte se presentan los principales proyectos de investigación que existen actualmente y las diferentes áreas de aplicación que tiene el Internet del Futuro. Y por último, en la cuarta parte, se realiza un análisis del concepto de privacidad y se estudian, mediante diferentes escenarios de aplicación, los riesgos que puede suponer para la privacidad la implantación del Internet de las Cosas. This paper consists of the preparation of a research project aimed to study the Internet of Things and the risks it poses to privacy. In recent years many projects have been launched and new technologies have been developed to make the Internet of Things a reality; however, critical issues such as security and privacy are not yet completely solved. The purpose of this project is to make a rigorous analysis of the Future Internet, increasing the knowledge acquired during the Masters, studying step by step the basis on which the Internet of Things is founded, and reflecting on the challenges it faces and the effects it can have on privacy. The project consists of 14 chapters structured in four parts. The first part consists of an introduction which explains the concepts of the Internet of Things and ubiquitous computing as a preamble to the next parts. Then, in the second part, technological and standardization issues of this new network are studied. The third part presents the main research projects and Internet of Things application areas. And finally, the fourth part includes an analysis of the privacy concept and also an evaluation of the risks the Internet of Things poses to privacy. These are examined through various application scenarios.

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Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications?it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ?Activity Monitor? has been designed and implemented: a personal health-persuasive application that provides feedback on the user?s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user?s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

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In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

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This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his real-time location and orientation and, finally, his active touch and focus interactions with the virtual overlay. The proposed reasoning method has been partially validated through a prototype that handles 2D and 3D visualization interfaces. This framework makes possible to develop in practice the IoT paradigm, augmenting the objects without physically modifying them.

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Improving energy efficiency in buildings is one of the goals of the Smart City initiatives and a challenge for the European Union. This paper presents a 6LoWPAN wireless transducer network (BatNet) as part of an open energy management system. This network has been designed to operate in buildings, to collect environmental information (temperature, humidity, illumination and presence) and electrical consumption in real time (voltage, current and power factor). The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM.