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.

Using the Journalistic Metaphor to Design User Interfaces That Explain Sensor Data

Facilitating general access to data from sensor networks (including traffic, hydrology and other domains) increases their utility. In this paper we argue that the journalistic metaphor can be effectively used to automatically generate multimedia presentations that help non-expert users analyze and understand sensor data. The journalistic layout and style are familiar to most users. Furthermore, the journalistic approach of ordering information from most general to most specific helps users obtain a high-level understanding while providing them the freedom to choose the depth of analysis to which they want to go. We describe the general characteristics and architectural requirements for an interactive intelligent user interface for exploring sensor data that uses the journalistic metaphor. We also describe our experience in developing this interface in real-world domains (e.g., hydrology).

SCA security verification on wireless sensor network node

Side Channel Attack (SCA) differs from traditional mathematic attacks. It gets around of the exhaustive mathematic calculation and precisely pin to certain points in the cryptographic algorithm to reveal confidential information from the running crypto-devices. Since the introduction of SCA by Paul Kocher et al [1], it has been considered to be one of the most critical threats to the resource restricted but security demanding applications, such as wireless sensor networks. In this paper, we focus our work on the SCA-concerned security verification on WSN (wireless sensor network). A detailed setup of the platform and an analysis of the results of DPA (power attack) and EMA (electromagnetic attack) is presented. The setup follows the way of low-cost setup to make effective SCAs. Meanwhile, surveying the weaknesses of WSNs in resisting SCA attacks, especially for the EM attack. Finally, SCA-Prevention suggestions based on Differential Security Strategy for the FPGA hardware implementation in WSN will be given, helping to get an improved compromise between security and cost.

Ontology-based access to sensor data streams

Sensor networks are increasingly becoming one of the main sources of Big Data on the Web. However, the observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse these data for other purposes than those for which they were originally set up. In this thesis we address these challenges, considering how we can transform streaming raw data to rich ontology-based information that is accessible through continuous queries for streaming data. Our main contribution is an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. We introduce novel query rewriting and data translation techniques that rely on mapping definitions relating streaming data models to ontological concepts. Specific contributions include: • The syntax and semantics of the SPARQLStream query language for ontologybased data access, and a query rewriting approach for transforming SPARQLStream queries into streaming algebra expressions. • The design of an ontology-based streaming data access engine that can internally reuse an existing data stream engine, complex event processor or sensor middleware, using R2RML mappings for defining relationships between streaming data models and ontology concepts. Concerning the sensor metadata of such streaming data sources, we have investigated how we can use raw measurements to characterize streaming data, producing enriched data descriptions in terms of ontological models. Our specific contributions are: • A representation of sensor data time series that captures gradient information that is useful to characterize types of sensor data. • A method for classifying sensor data time series and determining the type of data, using data mining techniques, and a method for extracting semantic sensor metadata features from the time series.

Enabling query technologies for the semantic sensor web

Sensor networks are increasingly being deployed in the environment for many different purposes. The observations that they produce are made available with heterogeneous schemas, vocabularies and data formats, making it difficult to share and reuse this data, for other purposes than those for which they were originally set up. The authors propose an ontology-based approach for providing data access and query capabilities to streaming data sources, allowing users to express their needs at a conceptual level, independent of implementation and language-specific details. In this article, the authors describe the theoretical foundations and technologies that enable exposing semantically enriched sensor metadata, and querying sensor observations through SPARQL extensions, using query rewriting and data translation techniques according to mapping languages, and managing both pull and push delivery modes.

Runtime variability for dynamic reconfiguration in wireless sensor network product lines

Runtime variability is a key technique for the success of Dynamic Software Product Lines (DSPLs), as certain application demand reconfiguration of system features and execution plans at runtime. In this emerging research work we address the problem of dynamic changes in feature models in sensor networks product families, where nodes of the network demand dynamic reconfiguration at post-deployment time.

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.

Deriving semantic sensor metadata from raw measurements

Sensor network deployments have become a primary source of big data about the real world that surrounds us, measuring a wide range of physical properties in real time. With such large amounts of heterogeneous data, a key challenge is to describe and annotate sensor data with high-level metadata, using and extending models, for instance with ontologies. However, to automate this task there is a need for enriching the sensor metadata using the actual observed measurements and extracting useful meta-information from them. This paper proposes a novel approach of characterization and extraction of semantic metadata through the analysis of sensor data raw observations. This approach consists in using approximations to represent the raw sensor measurements, based on distributions of the observation slopes, building a classi?cation scheme to automatically infer sensor metadata like the type of observed property, integrating the semantic analysis results with existing sensor networks metadata.

Wake-up architecture for Wireless sensor nodes based on ultra low power FPGA

In this work a novel wake-up architecture for wireless sensor nodes based on ultra low power FPGA is presented. A simple wake up messaging mechanism for data gathering applications is proposed. The main goal of this work is to evaluate the utilization of low power configurable devices to take advantage of their speed, flexibility and low power consumption compared with traditional approaches, based on ASICs or microcontrollers, for frame decoding and data control. A test bed based on infrared communications has been built to validate the messaging mechanism and the processing architecture.

Propuesta de aplicación de una red de sensores en emergencias

El auge y evolución de los sistemas de comunicaciones móviles y de las redes inalámbricas avanzadas, sucedido desde principios del siglo XXI, han propiciado el uso de Redes de Sensores Inalámbricos (RSI) en múltiples ámbitos de interés. Dichas redes están típicamente compuestas por dispositivos inalámbricos autónomos que incorporan sensores para la recogida de datos de distinta naturaleza. Las RSI se caracterizan por su escalabilidad, ausencia de cableado, pequeño tamaño, bajo consumo, gran variedad de magnitudes físico/químicas medibles, entre otras, cuyas cualidades las hace muy interesantes para su aplicación en multitud de escenarios de la Sociedad de la Información, tales como domótica, agricultura y ganadería, medioambiente, salud, procesos industriales, logística, seguridad o ciudades inteligentes, ente otras. En este Trabajo Fin de Máster, se propone el uso de las RSI en el escenario de Emergencias donde cobra gran importancia la usabilidad, la fiabilidad, la disponibilidad, y la robustez de los sistemas a emplear en condiciones hostiles, especialmente en las de bomberos. Es por ello que se analizarán previamente los trabajos de RSI desarrollados para estos entornos y que sugieren qué aplicaciones garantizan el cumplimiento de los requerimientos mencionados. Se aborda la utilización de una primera RSI para la monitorización ambiental de tres Centros de Procesado de Datos (CPD) del departamento de TI de Emergencias, siendo este un entorno sin movilidad, más controlado y que aporta la adquisición de experiencia en la utilización de las RSI de cara a un entorno móvil más complejo. A continuación, para el entorno móvil se ha desarrollado y validado un prototipo experimental de RSI para el seguimiento de salida de parques de bomberos de vehículos con su dotación. Así mismo se implementa un prototipo para la ayuda a la localización de bomberos y/o personas en un siniestro. Estas RSI se desarrollan e implantan en el entorno de Emergencias del Ayuntamiento de Madrid, entidad sin cuyo apoyo habría sido imposible la aplicación práctica de este trabajo. SUMMARY. The rise and evolution of mobile communication systems and advanced wireless networks in early XXI century have allowed to taking advantage of Wireless Sensor Networks (WSN). These networks are composed of independent wireless devices that incorporate sensors for collecting data of different nature. The WSN is characterized by its scalability, no wiring, small size, low power consumption, wide range of physical magnitudes measurable, among others. These qualities make them very interesting for application in many scenarios to the Information Society, such as, domotic, agriculture, smart environment, ehealth, industrial control, logistics, security and smart cities, among others. This work proposes to use WSN in the emergency scenario where is very important the usability, reliability, availability, and robustness of the systems to be used in hostile conditions, especially in fire-fighters environment. That is why WSN works in emergency will be studied to tackle what applications compliance with the above requirements. The first WSN developed will be environmental monitoring of three CPDs IT department Emergency. This scenario is a non-mobile environment, more controlled and bring gaining experience in the use of WSN to face mobile environment which is more complex. Then, for the mobile environment is developed an experimental prototype of WSN for tracking fire vehicles living fire stations with their equipment. Another prototype is foreseen to be implemented to assist fire-fighters location and / or people in a disaster. These WSN are developed and implemented for Madrid City Emergency, whose involvement was critical to put this research into stage.

Integration of wearable devices in a wireless sensor network for an e-health application

Applications based on Wireless Sensor Networks for Internet of Things scenarios are on the rise. The multiple possibilities they offer have spread towards previously hard to imagine fields, like e-health or human physiological monitoring. An application has been developed for its usage in scenarios where data collection is applied to smart spaces, aiming at its usage in fire fighting and sports. This application has been tested in a gymnasium with real, non-simulated nodes and devices. A Graphic User Interface has been implemented to suggest a series of exercises to improve a sportsman/woman s condition, depending on the context and their profile. This system can be adapted to a wide variety of e-health applications with minimum changes, and the user will interact using different devices, like smart phones, smart watches and/or tablets.

Wireless Sensor Network Solution for Sustainable Food Production

Environmental monitoring has become a key aspect in food production over the last few years. Due to their low cost, low power consumption and flexibility, Wireless Sensor Networks (WSNs) have turned up as a very convenient tool to be used in these environments where no intrusion is a must. In this work, a WSN application in a food factory is presented. The paper gives an overview of the system set up, covering from the initial study of the parameters and sensors, to the hardware-software design and development needed for the final tests in the factory facilities.

A reliable support tool for monitoring, testing and debugging wireless sensor cookie nodes

In this work a WSN Support Tool for developing, testing, monitoring and debugging new application prototypes in a reliable and robust way is proposed, by combining a Hardware -Software Integration Platform with the implementation of a parallel communication channel that helps users to interact to the experiments in runtime without interfering in the operation of the wireless network. As a pre-deployment tool, prototypes can be validated in a real environment before implementing them in the final application, aiming to increase the effectiveness and efficiency of the technology. This infrastructure is the support of CookieLab: a WSN testbed based on the Cookie Nodes Platform.

Sistemas de gestión de sensores mediante tecnologías M2M

En el proyecto se lleva a cabo un estudio práctico sobre dos escenarios donde intervienen dispositivos relacionados con el Internet de las cosas. También se puede situar como una solución de comunicación M2M. Comunicación máquina a máquina implica un sistema central que es capaz de conectarse con otros sistemas en varios lugares. La conexión permite que el sistema central recoja o envíe datos a cada lugar remoto para su procesamiento. El primer escenario consta de la configuración y montaje de un microcontrolador conocido como Waspmote que se encarga de recoger variables atmosféricas gracias a un conjunto de sensores y enviar los datos a un router multiprotocolo Meshlium mediante tecnología Zigbee, un tipo de red orientada a redes de sensores. Este montaje tiene como fin instalar una estación meteorológica en el campus de la universidad y poder almacenar y administrar sus datos. La segunda parte dos dispositivos de hardware libre como son un Arduino con capacidad GPRS y una RaspberryPi conectada a la red cableada enviaran datos por ejemplo de temperatura y luminosidad a una red social de sensores conocida como Xively, gestionaremos nuestros dispositivos sobre esta plataforma gratuita, que nos permite dar de alta dispositivos, almacenar y representar los datos en tiempo real y consultarlos vía Web o mediante una aplicación móvil realizada para este caso por medio de funciones ofrecidas por Xively. He diseñado una aplicación Android que permite la consulta de datos y administración de sensores por un usuario, intenta abstraer al usuario de la complejidad técnica y acercar los objetos conectados, en este caso sensores. Se han detallado las configuraciones y el proceso de instalación de todos los dispositivos. Se explican conceptos para entender las tecnologías de comunicación, Zigbee y Http, este protocolo participara a nivel de aplicación realizando peticiones o enviando datos, administrando la capacidad y por tanto ahorro. ABSTRACT. The project takes a practical study on two scenarios which involved related to the Internet of Things devices. It can also be placed as a M2M communication solution. Machine to machine communication involves a central system that is able to connect with other systems in several places. The connection allows the central system to collect or send data to each remote location for processing. The first stage consists of the configuration and setup of a microcontroller known as Waspmote which is responsible to collect atmospheric variables by a set of sensors and send the data to a multiprotocol router Meshlium by Zigbee technology, a type of sensor networks oriented network. This assembly aims to set up a weather station on the campus of the university and to store and manage their data. The second part two devices free hardware like Arduino with GPRS capacity and RaspberryPi connected to the wired network send data, temperature and luminosity to a social network of sensors known as Xively, manage our devices on this free platform, which allows us to register devices, store and display data in real time and consult the web or through a mobile application on this case by means of functions offered by Xively. I have designed an Android application that allows data consultation and management of sensors by a user, the user tries to abstract the technical complexity and bring the connected objects, in this case sensors. Were detailed settings and the installation of all devices. Concepts are explained to understand communication technologies, Zigbee and Http, this protocol participate performing application-level requests or sending data, managing capacity and therefore savings.

Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.