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.

The SSN ontology of the W3C semantic sensor network incubator group

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations ? the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.

Validez y fiabilidad del sensor láser del sistema BioLaserSport® para el análisis de la velocidad de la carrera

El análisis de la velocidad de carrera mediante sensores láser permite la obtención de datos en tiempo real siendo ventajosos frente a otros sistemas. El objetivo de este estudio fue valorar la validez y fiabilidad del sensor láser del sistema BioLaserSport® para el cálculo de velocidades medias y máximas mediante estadísticos relativos y absolutos. Los participantes fueron 17 varones (20.85 ± 1.54 años). Se utilizó un sensor láser tipo 1 (LDM301, Jenoptik, Germany) que registró posiciones de los deportistas a 2000 Hz. Los datos se trataron con la rutina DSL-30 creada con DasyLab v.10.0. Para la validación se utilizó un sistema de fotogrametría-2D con una cámara de alta velocidad (Exilim High Speed EX-F1, Casio) y SkillSpector v.1.3.2. (Video4coach, Grubbemollevej). Además, se utilizaron foto-células de doble haz (Polifemo Light, Microgate, Italy) y un cronómetro Racetime2 (Microgate, Italy). Se registraron, durante dos días, tres series de 30 m de carrera a máxima velocidad. El sensor láser proporcionó, con relación a la fotogrametría, diferencias en las velocidades medias y máximas de -0.11 m•s-1 y 0.14 m•s-1, respectivamente, con unos coeficientes de correlación superiores a 0.86, y mayores de 0.92 con las foto-células para las velocidades medias. Este mostró una excelente fiabilidad test-retest para las velocidades medias con un coeficiente de correlación intraclase (ICC) entre 0.7-0.9 y un error estándar de la media (SEM y SEM%), intrasesión e intersesión, menor de 0.05 m•s-1 y 0.12 m•s-1, respectivamente, y menores de 0.75% y de 2%, respectivamente. Para las velocidades máximas,los valores fueron menores de 0.10 m•s-1 y 0.17 m•s-1, respectivamente, y en ambos casos menores a 1.36% y 1,89%. El láser fue capaz de identificar mínimos cambios detectables (MDC y MDC%) intrasesión, para ambas variables, menores a 0.14 m•s-1 y 0.29 m•s-1, respectivamente (< 2.09% y < 3.76%) e intersesión, menores de 0.34 m•s-1 y 0.47 m•s-1 (< 5.56% y < 5.25%), respectivamente. En consecuencia, es un instrumento útil para el análisis de la evolución de la velocidad intrasujeto y entre sujetos en la carrera de velocidad entre 0-30 m, proporcionando resultados en tiempo real, pero se han de considerar los SEM, SEM%, MDC y MDC% para valorar la mejora del rendimiento.

Magneto-optic current sensor with Faraday mirror for linear birefringence compensation

Fiber optic sensors have some advantages in subjects related with electrical current and magnetic field measurement. In spite of the optical fiber utilization advantages we have to take into account undesirable effects, which are present in real non-ideal optical fibers. In telecommunication and sensor application fields the presence of inherent and induced birefringence is crucial. The presence of birefringence may cause an undesirable change in the polarization state. In order to compensate the linear birefringence a promising method has been chosen. This method employs orthogonal polarization conjugation in the back propagation direction of the light wave in the fiber. A study and a simulation of an experimental setup are realized with the advantage of a significant sensitivity improvement.

A practical approach for outdoors distributed target localization in wireless sensor networks

Wireless sensor networks are posed as the new communication paradigm where the use of small, low-complexity, and low-power devices is preferred over costly centralized systems. The spectra of potential applications of sensor networks is very wide, ranging from monitoring, surveillance, and localization, among others. Localization is a key application in sensor networks and the use of simple, efficient, and distributed algorithms is of paramount practical importance. Combining convex optimization tools with consensus algorithms we propose a distributed localization algorithm for scenarios where received signal strength indicator readings are used. We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node. The formulated problem is solved by a relaxed version using semidefinite relaxation technique. Conditions under which the relaxed problem yields to the same solution as the original problem are given and a distributed consensusbased implementation of the algorithm is proposed based on an augmented Lagrangian approach and primaldual decomposition methods. Although suboptimal, the proposed approach is very suitable for its implementation in real sensor networks, i.e., it is scalable, robust against node failures and requires only local communication among neighboring nodes. Simulation results show that running an additional local search around the found solution can yield performance close to the maximum likelihood estimate.

Detecting unknown attacks in wireless sensor networks that contain mobile nodes

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

Self-healing in unattended wireless sensor networks

Wireless sensor networks (WSNs) appeal to a wide range of applications that involve the monitoring of various physical phenomena. However, WSNs are subject to many threats. In particular, lack of pervasive tamper-resistant hardware results in sensors being easy targets for compromise. Having compromised a sensor, the adversary learns all the sensor secrets, allowing it to later encrypt/decrypt or authenticate messages on behalf of that sensor. This threat is particularly relevant in the novel unattended wireless sensor networks (UWSNs) scenario. UWSNs operate without constant supervision by a trusted sink. UWSN?s unattended nature and increased exposure to attacks prompts the need for special techniques geared towards regaining security after being compromised. In this article, we investigate cooperative self-healing in UWSNs and propose various techniques to allow unattended sensors to recover security after compromise. Our techniques provide seamless healing rates even against a very agile and powerful adversary. The effectiveness and viability of our proposed techniques are assessed by thorough analysis and supported by simulation results. Finally, we introduce some real-world issues affecting UWSN deployment and provide some solutions for them as well as a few open problems calling for further investigation.

Secure neighbor discovery in wireless sensor networks using range-free localization techniques

Si una red inalámbrica de sensores se implementa en un entorno hostil, las limitaciones intrínsecas a los nodos conllevan muchos problemas de seguridad. En este artículo se aborda un ataque particular a los protocolos de localización y descubrimiento de vecinos, llevada a cabo por dos nodos que actúan en connivencia y establecen un "agujero de gusano" para tratar de engañar a un nodo aislado, haciéndole creer que se encuentra en la vecindad de un conjunto de nodos locales. Para contrarrestar este tipo de amenazas, se presenta un marco de actuación genéricamente denominado "detection of wormhole attacks using range-free methods" (DWARF) dentro del cual derivamos dos estrategias para de detección de agujeros de gusano: el primer enfoque (DWARFLoc) realiza conjuntamente la localización y la detección de ataques, mientras que el otro (DWARFTest) valida la posición estimada por el nodo una vez finalizado el protocolo de localización. Las simulaciones muestran que ambas estrategias son eficaces en la detección de ataques tipo "agujero de gusano", y sus prestaciones se comparan con las de un test convencional basado en la razón de verosimilitudes.

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.

Lifetime maximization for beamforming applications in wireless sensor networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

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.

Sensor magneto-óptico de corriente con supresión de birrefringencia lineal mediante espejo de Faraday

Fiber optic sensors have some advantages in subjects related with electrical current and magnetic field measurement. In spite of the optical fiber utilization advantages we have to take into account undesirable effects, which are present in real non-ideal optical fibers. In telecommunication and sensor application fields the presence of inherent and induced birefringence is crucial. The presence of birefringence may cause an undesirable change in the polarization state. In order to compensate the linear birefringence a promising method has been chosen. This method employs orthogonal polarization conjugation in the back propagation direction of the light wave in the fiber. A study and a simulation of an experimental setup are realized with the advantage of a significant sensitivity improvement.

Temperature Sensor Placement Including Routing Overhead and Sampling Inaccuracies

Dynamic thermal management techniques require a collection of on-chip thermal sensors that imply a significant area and power overhead. Finding the optimum number of temperature monitors and their location on the chip surface to optimize accuracy is an NP-hard problem. In this work we improve the modeling of the problem by including area, power and networking constraints along with the consideration of three inaccuracy terms: spatial errors, sampling rate errors and monitor-inherent errors. The problem is solved by the simulated annealing algorithm. We apply the algorithm to a test case employing three different types of monitors to highlight the importance of the different metrics. Finally we present a case study of the Alpha 21364 processor under two different constraint scenarios.

Smart parking service based on wireless sensor networks

n this paper, we present the design and implementation of a prototype system of Smart Parking Services based on Wireless Sensor Networks (WSNs) that allows vehicle drivers to effectively find the free parking places. The proposed scheme consists of wireless sensor networks, embedded web-server, central web-server and mobile phone application. In the system, low-cost wireless sensors networks modules are deployed into each parking slot equipped with one sensor node. The state of the parking slot is detected by sensor node and is reported periodically to embedded web-server via the deployed wireless sensor networks. This information is sent to central web-server using Wi-Fi networks in real-time, and also the vehicle driver can find vacant parking lots using standard mobile devices.

Simulation Tool and Case Study for Planning Wireless Sensor Network

In this paper, a simulation tool for assisting the deployment of wireless sensor network is introduced and simulation results are verified under a specific indoor environment. The simulation tool supports two modes: deterministic mode and stochastic mode. The deterministic mode is environment dependent in which the information of environment should be provided beforehand. Ray tracing method and deterministic propagation model are employed in order to increase the accuracy of the estimated coverage, connectivity and routing; the stochastic mode is useful for large scale random deployment without previous knowledge on geographic information. Dynamic Source Routing protocol (DSR) and Ad hoc On-Demand Distance Vector Routing protocol (AODV) are implemented in order to calculate the topology of WSN. Hence this tool gives direct view on the performance of WSN and assists users in finding the potential problems of wireless sensor network before real deployment. At the end, a case study is realized in Centro de Electronica Industrial (CEI), the simulation results on coverage, connectivity and routing are verified by the measurement.