Monitoreo de condiciones de higiene y seguridad del ambiente en entornos industriales usando redes de sensores inalámbricos

Resumen: Las redes de sensores inalámbricos han atraído mucha atención en los últimos años debido a la integración de tecnología inalámbrica, computación y tecnología de sensores. Estas redes consisten en una serie de nodos equipados con capacidades de procesamiento, comunicación y sensado. Utilizan protocolos especiales de radio para transmitir datos en un modo multisalto de operación. En este trabajo se propone utilizar una red de sensores para el monitoreo de las condiciones ambientales de Higiene y Seguridad en entornos industriales. Concretamente se monitorean Temperatura, Humedad, Ruido y Luminosidad. Se propone esta recolección de datos para dar soporte a la inspección anual de un auditor externo, por lo que no se considera esta recolección como crítica dado que no controlan ningún dispositivo. En primera instancia se aborda el problema utilizando una red de sensores con módulos que utilizan el protocolo 802.15 los cuales transmiten a un nodo maestro que sirve como gateway para enviar la información a un servidor que la almacena. La recolección de datos se realiza a través de una plataforma arduino como interface entre el módulo inalámbrico y los sensores. Esta primera propuesta es contrastada con un enfoque de Internet de las Cosas (IoT) utilizando módulos Arduino con WiFi embebido, denominados Wido, que permiten la comunicación de datos directamente al servidor de almacenaje. El trabajo comprende la caracterización del problema, elección del hardware, diseño de la red y la realización de pruebas para evaluar el funcionamiento de ambos enfoques.

Nonparametric Message Passing Methods for Cooperative Localization and Tracking

The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

Intrusion-Resilient Integrity in Data-Centric Unattended WSNs

Unattended Wireless Sensor Networks (UWSNs) operate in autonomous or disconnected mode: sensed data is collected periodically by an itinerant sink. Between successive sink visits, sensor-collected data is subject to some unique vulnerabilities. In particular, while the network is unattended, a mobile adversary (capable of subverting up to a fraction of sensors at a time) can migrate between compromised sets of sensors and inject fraudulent data. In this paper, we provide two collaborative authentication techniques that allow an UWSN to maintain integrity and authenticity of sensor data-in the presence of a mobile adversary-until the next sink visit. Proposed schemes use simple, standard, and inexpensive symmetric cryptographic primitives, coupled with key evolution and few message exchanges. We study their security and effectiveness, both analytically and via simulations. We also assess their robustness and show how to achieve the desired trade-off between performance and security.

PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure.

Participatory Sensing combines the ubiquity of mobile phones with sensing capabilities of Wireless Sensor Networks. It targets pervasive collection of information, e.g., temperature, traffic conditions, or health-related data. As users produce measurements from their mobile devices, voluntary participation becomes essential. However, a number of privacy concerns -- due to the personal information conveyed by data reports -- hinder large-scale deployment of participatory sensing applications. Prior work on privacy protection, for participatory sensing, has often relayed on unrealistic assumptions and with no provably-secure guarantees. The goal of this project is to introduce PEPSI: a Privacy-Enhanced Participatory Sensing Infrastructure. We explore realistic architectural assumptions and a minimal set of (formal) privacy requirements, aiming at protecting privacy of both data producers and consumers. We design a solution that attains privacy guarantees with provable security at very low additional computational cost and almost no extra communication overhead.

Redes y servicios ubicuos para Internet de las Cosas en dispositivos llevables

En las últimas décadas se han producido importantes avances tecnológicos, lo que ha producido un crecimiento importante de las Redes Inalámbricas de Sensores (RIS), conocidas en inglés como Wireless Sensor Networks (WSN). Estas redes están formadas por un conjunto de pequeños nodos o también, conocidos como motas, compuestos por diversos tipos de sensores. Las Redes Inalámbricas de Sensores pueden resultar muy útiles en entornos donde el despliegue de redes cableadas, formadas por ordenadores, encaminadores u otros dispositivos de red no sea posible. Sin embargo, este tipo de redes presentan una serie de carencias o problemas que dificultan, en ocasiones, su implementación y despliegue. Este Proyecto Fin de Carrera tiene como principales objetivos: diseñar e implementar un agente que haga uso de la tecnología Bluetooth para que se pueda comunicar tanto con la arquitectura orientada a servicios, vía radio, como con el módulo Bioharness para obtener parámetros fisiológicos; ofrecer una serie de servicios simples a la Red Inalámbrica de Sensores; diseñar un algoritmo para un sistema de alarmas; realizar e implementar una pasarela entre protocolos que usen el estándar IEEE802.15.4 (ZigBee) y el estándar IEEE802.15.1 de la Tecnología Bluetooth. Por último, implementar una aplicación Android para el reloj WiMM y que este pueda recibir alarmas en tiempo real a través del la Interfaz Bluetooth. Para lograr estos objetivos, en primer lugar realizaremos un estudio del Estado del Arte de las Redes Inalámbricas de Sensores, con el fin de estudiar su arquitectura, el estándar Bluetooth y los dispositivos Bluetooth que se han utilizado en este Proyecto. Seguidamente, describiremos detalladamente el firmware iWRAP versión 4, centrándonos en sus modos de operación, comandos AT y posibles errores que puedan ocurrir. A continuación, se describirá la arquitectura y la especificación nSOM, para adentrarnos en la arquitectura orientada a servicios. Por último, ejecutaremos la fase de validación del sistema y se analizarán los resultados obtenidos durante la fase de pruebas. ABSTRACT In last decades there have been significant advances in technology, which has resulted in important growth of Wireless Sensor Networks (WSN). These networks consist of a small set of nodes, also known as spots; equipped with various types of sensors. Wireless Sensor Networks can be very useful in environments where deployment of wired networks, formed by computers, routers or other network devices is not possible. However, these networks have a number of shortcomings or challenges to, sometimes, their implementation and deployment. The main objectives of this Final Project are to design and implement an agent that makes use of Bluetooth technology so you can communicate with both the service-oriented architecture, via radio, as with Bioharness module for physiological parameters; offer simple services to Wireless Sensor Network, designing an algorithm for an alarm system, make and implement a gateway between protocols using the standard IEEE802.15.4 (ZigBee) and IEEE802.15.1 standard Bluetooth Technology. Finally, implement an Android application for WiMM watch that can receive real-time alerts through the Bluetooth interface. In order to achieve these objectives, firstly we are going to carry out a study of the State of the Art in Wireless Sensor Network, where we study the architecture, the Bluetooth standard and Bluetooth devices that have been used in this project. Then, we will describe in detail the iWRAP firmware version 4, focusing on their operation modes, AT commands and errors that may occur. Therefore, we will describe the architecture and specification nSOM, to enter into the service-oriented architecture. Finally, we will execute the phase of validation of the system in a real application scenario, analyzing the results obtained during the testing phase.

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain.

StreamCloud: An Elastic Parallel-Distributed Stream Processing Engine

In recent years, applications in domains such as telecommunications, network security or large scale sensor networks showed the limits of the traditional store-then-process paradigm. In this context, Stream Processing Engines emerged as a candidate solution for all these applications demanding for high processing capacity with low processing latency guarantees. With Stream Processing Engines, data streams are not persisted but rather processed on the fly, producing results continuously. Current Stream Processing Engines, either centralized or distributed, do not scale with the input load due to single-node bottlenecks. Moreover, they are based on static configurations that lead to either under or over-provisioning. This Ph.D. thesis discusses StreamCloud, an elastic paralleldistributed stream processing engine that enables for processing of large data stream volumes. Stream- Cloud minimizes the distribution and parallelization overhead introducing novel techniques that split queries into parallel subqueries and allocate them to independent sets of nodes. Moreover, Stream- Cloud elastic and dynamic load balancing protocols enable for effective adjustment of resources depending on the incoming load. Together with the parallelization and elasticity techniques, Stream- Cloud defines a novel fault tolerance protocol that introduces minimal overhead while providing fast recovery. StreamCloud has been fully implemented and evaluated using several real word applications such as fraud detection applications or network analysis applications. The evaluation, conducted using a cluster with more than 300 cores, demonstrates the large scalability, the elasticity and fault tolerance effectiveness of StreamCloud. Resumen En los útimos años, aplicaciones en dominios tales como telecomunicaciones, seguridad de redes y redes de sensores de gran escala se han encontrado con múltiples limitaciones en el paradigma tradicional de bases de datos. En este contexto, los sistemas de procesamiento de flujos de datos han emergido como solución a estas aplicaciones que demandan una alta capacidad de procesamiento con una baja latencia. En los sistemas de procesamiento de flujos de datos, los datos no se persisten y luego se procesan, en su lugar los datos son procesados al vuelo en memoria produciendo resultados de forma continua. Los actuales sistemas de procesamiento de flujos de datos, tanto los centralizados, como los distribuidos, no escalan respecto a la carga de entrada del sistema debido a un cuello de botella producido por la concentración de flujos de datos completos en nodos individuales. Por otra parte, éstos están basados en configuraciones estáticas lo que conducen a un sobre o bajo aprovisionamiento. Esta tesis doctoral presenta StreamCloud, un sistema elástico paralelo-distribuido para el procesamiento de flujos de datos que es capaz de procesar grandes volúmenes de datos. StreamCloud minimiza el coste de distribución y paralelización por medio de una técnica novedosa la cual particiona las queries en subqueries paralelas repartiéndolas en subconjuntos de nodos independientes. Ademas, Stream- Cloud posee protocolos de elasticidad y equilibrado de carga que permiten una optimización de los recursos dependiendo de la carga del sistema. Unidos a los protocolos de paralelización y elasticidad, StreamCloud define un protocolo de tolerancia a fallos que introduce un coste mínimo mientras que proporciona una rápida recuperación. StreamCloud ha sido implementado y evaluado mediante varias aplicaciones del mundo real tales como aplicaciones de detección de fraude o aplicaciones de análisis del tráfico de red. La evaluación ha sido realizada en un cluster con más de 300 núcleos, demostrando la alta escalabilidad y la efectividad tanto de la elasticidad, como de la tolerancia a fallos de StreamCloud.

Intelligent context-aware services based on internet of things architectures

La Internet de las Cosas (IoT), como parte de la Futura Internet, se ha convertido en la actualidad en uno de los principales temas de investigación; en parte gracias a la atención que la sociedad está poniendo en el desarrollo de determinado tipo de servicios (telemetría, generación inteligente de energía, telesanidad, etc.) y por las recientes previsiones económicas que sitúan a algunos actores, como los operadores de telecomunicaciones (que se encuentran desesperadamente buscando nuevas oportunidades), al frente empujando algunas tecnologías interrelacionadas como las comunicaciones Máquina a Máquina (M2M). En este contexto, un importante número de actividades de investigación a nivel mundial se están realizando en distintas facetas: comunicaciones de redes de sensores, procesado de información, almacenamiento de grandes cantidades de datos (big--‐data), semántica, arquitecturas de servicio, etc. Todas ellas, de forma independiente, están llegando a un nivel de madurez que permiten vislumbrar la realización de la Internet de las Cosas más que como un sueño, como una realidad tangible. Sin embargo, los servicios anteriormente mencionados no pueden esperar a desarrollarse hasta que las actividades de investigación obtengan soluciones holísticas completas. Es importante proporcionar resultados intermedios que eviten soluciones verticales realizadas para desarrollos particulares. En este trabajo, nos hemos focalizado en la creación de una plataforma de servicios que pretende facilitar, por una parte la integración de redes de sensores y actuadores heterogéneas y geográficamente distribuidas, y por otra lado el desarrollo de servicios horizontales utilizando dichas redes y la información que proporcionan. Este habilitador se utilizará para el desarrollo de servicios y para la experimentación en la Internet de las Cosas. Previo a la definición de la plataforma, se ha realizado un importante estudio focalizando no sólo trabajos y proyectos de investigación, sino también actividades de estandarización. Los resultados se pueden resumir en las siguientes aseveraciones: a) Los modelos de datos definidos por el grupo “Sensor Web Enablement” (SWE™) del “Open Geospatial Consortium (OGC®)” representan hoy en día la solución más completa para describir las redes de sensores y actuadores así como las observaciones. b) Las interfaces OGC, a pesar de las limitaciones que requieren cambios y extensiones, podrían ser utilizadas como las bases para acceder a sensores y datos. c) Las redes de nueva generación (NGN) ofrecen un buen sustrato que facilita la integración de redes de sensores y el desarrollo de servicios. En consecuencia, una nueva plataforma de Servicios, llamada Ubiquitous Sensor Networks (USN), se ha definido en esta Tesis tratando de contribuir a rellenar los huecos previamente mencionados. Los puntos más destacados de la plataforma USN son: a) Desde un punto de vista arquitectónico, sigue una aproximación de dos niveles (Habilitador y Gateway) similar a otros habilitadores que utilizan las NGN (como el OMA Presence). b) Los modelos de datos están basado en los estándares del OGC SWE. iv c) Está integrado en las NGN pero puede ser utilizado sin ellas utilizando infraestructuras IP abiertas. d) Las principales funciones son: Descubrimiento de sensores, Almacenamiento de observaciones, Publicacion--‐subscripcion--‐notificación, ejecución remota homogénea, seguridad, gestión de diccionarios de datos, facilidades de monitorización, utilidades de conversión de protocolos, interacciones síncronas y asíncronas, soporte para el “streaming” y arbitrado básico de recursos. Para demostrar las funcionalidades que la Plataforma USN propuesta pueden ofrecer a los futuros escenarios de la Internet de las Cosas, se presentan resultados experimentales de tres pruebas de concepto (telemetría, “Smart Places” y monitorización medioambiental) reales a pequeña escala y un estudio sobre semántica (sistema de información vehicular). Además, se está utilizando actualmente como Habilitador para desarrollar tanto experimentación como servicios reales en el proyecto Europeo SmartSantander (que aspira a integrar alrededor de 20.000 dispositivos IoT). v Abstract Internet of Things, as part of the Future Internet, has become one of the main research topics nowadays; in part thanks to the pressure the society is putting on the development of a particular kind of services (Smart metering, Smart Grids, eHealth, etc.), and by the recent business forecasts that situate some players, like Telecom Operators (which are desperately seeking for new opportunities), at the forefront pushing for some interrelated technologies like Machine--‐to--‐Machine (M2M) communications. Under this context, an important number of research activities are currently taking place worldwide at different levels: sensor network communications, information processing, big--‐ data storage, semantics, service level architectures, etc. All of them, isolated, are arriving to a level of maturity that envision the achievement of Internet of Things (IoT) more than a dream, a tangible goal. However, the aforementioned services cannot wait to be developed until the holistic research actions bring complete solutions. It is important to come out with intermediate results that avoid vertical solutions tailored for particular deployments. In the present work, we focus on the creation of a Service--‐level platform intended to facilitate, from one side the integration of heterogeneous and geographically disperse Sensors and Actuator Networks (SANs), and from the other the development of horizontal services using them and the information they provide. This enabler will be used for horizontal service development and for IoT experimentation. Prior to the definition of the platform, we have realized an important study targeting not just research works and projects, but also standardization topics. The results can be summarized in the following assertions: a) Open Geospatial Consortium (OGC®) Sensor Web Enablement (SWE™) data models today represent the most complete solution to describe SANs and observations. b) OGC interfaces, despite the limitations that require changes and extensions, could be used as the bases for accessing sensors and data. c) Next Generation Networks (NGN) offer a good substrate that facilitates the integration of SANs and the development of services. Consequently a new Service Layer platform, called Ubiquitous Sensor Networks (USN), has been defined in this Thesis trying to contribute to fill in the previous gaps. The main highlights of the proposed USN Platform are: a) From an architectural point of view, it follows a two--‐layer approach (Enabler and Gateway) similar to other enablers that run on top of NGN (like the OMA Presence). b) Data models and interfaces are based on the OGC SWE standards. c) It is integrated in NGN but it can be used without it over open IP infrastructures. d) Main functions are: Sensor Discovery, Observation Storage, Publish--‐Subscribe--‐Notify, homogeneous remote execution, security, data dictionaries handling, monitoring facilities, authorization support, protocol conversion utilities, synchronous and asynchronous interactions, streaming support and basic resource arbitration. vi In order to demonstrate the functionalities that the proposed USN Platform can offer to future IoT scenarios, some experimental results have been addressed in three real--‐life small--‐scale proofs--‐of concepts (Smart Metering, Smart Places and Environmental monitoring) and a study for semantics (in--‐vehicle information system). Furthermore we also present the current use of the proposed USN Platform as an Enabler to develop experimentation and real services in the SmartSantander EU project (that aims at integrating around 20.000 IoT devices).

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

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.

StreamCloud: An elastic and scalable data streaming system

Many applications in several domains such as telecommunications, network security, large scale sensor networks, require online processing of continuous data lows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static con?gurations that lead to either under or over-provisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation and a thorough evaluation of the scalability and elasticity of the fully implemented system.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

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.

Towards a fuzzy-based multi-classifier selection module for activity recognition applications

Performing activity recognition using the information provided by the different sensors embedded in a smartphone face limitations due to the capabilities of those devices when the computations are carried out in the terminal. In this work a fuzzy inference module is implemented in order to decide which classifier is the most appropriate to be used at a specific moment regarding the application requirements and the device context characterized by its battery level, available memory and CPU load. The set of classifiers that is considered is composed of Decision Tables and Trees that have been trained using different number of sensors and features. In addition, some classifiers perform activity recognition regardless of the on-body device position and others rely on the previous recognition of that position to use a classifier that is trained with measurements gathered with the mobile placed on that specific position. The modules implemented show that an evaluation of the classifiers allows sorting them so the fuzzy inference module can choose periodically the one that best suits the device context and application requirements.

Distributed target tracking based on belief propagation consensus

Distributed target tracking in wireless sensor networks (WSN) is an important problem, in which agreement on the target state can be achieved using conventional consensus methods, which take long to converge. We propose distributed particle filtering based on belief propagation (DPF-BP) consensus, a fast method for target tracking. According to our simulations, DPF-BP provides better performance than DPF based on standard belief consensus (DPF-SBC) in terms of disagreement in the network. However, in terms of root-mean square error, it can outperform DPF-SBC only for a specific number of consensus iterations.

Short paper: From streaming data to linked data. A case study with bike sharing systems

Current methods and tools that support Linked Data publication have mainly focused so far on static data, without considering the growing amount of streaming data available on the Web. In this paper we describe a case study that involves the publication of static and streaming Linked Data for bike sharing systems and related entities. We describe some of the challenges that we have faced, the solutions that we have explored, the lessons that we have learned, and the opportunities that lie in the future for exploiting Linked Stream Data.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.