FPGA-Based Wireless Sensor Node Architecture for High Performance Applications

While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements.

NFC based remote control of services for interactive spaces

Ubiquitous computing (one person, many computers) is the third era in the history of computing. It follows the mainframe era (many people, one computer) and the PC era (one person, one computer). Ubiquitous computing empowers people to communicate with services by interacting with their surroundings. Most of these so called smart environments contain sensors sensing users’ actions and try to predict the users’ intentions and necessities based on sensor data. The main drawback of this approach is that the system might perform unexpected or unwanted actions, making the user feel out of control. In this master thesis we propose a different procedure based on Interactive Spaces: instead of predicting users’ intentions based on sensor data, the system reacts to users’ explicit predefined actions. To that end, we present REACHeS, a server platform which enables communication among services, resources and users located in the same environment. With REACHeS, a user controls services and resources by interacting with everyday life objects and using a mobile phone as a mediator between himself/herself, the system and the environment. REACHeS’ interfaces with a user are built upon NFC (Near Field Communication) technology. NFC tags are attached to objects in the environment. A tag stores commands that are sent to services when a user touches the tag with his/her NFC enabled device. The prototypes and usability tests presented in this thesis show the great potential of NFC to build such user interfaces.

Hidrodinamica de planeadores submarinos y su impacto en la funcionalidad de sensores CTD

Los recientes desarrollos tecnológicos permiten la transición de la oceanografía observacional desde un concepto basado en buques a uno basado en sistemas autónomos en red. Este último, propone que la forma más eficiente y efectiva de observar el océano es con una red de plataformas autónomas distribuidas espacialmente y complementadas con sistemas de medición remota. Debido a su maniobrabilidad y autonomía, los planeadores submarinos están jugando un papel relevante en este concepto de observaciones en red. Los planeadores submarinos fueron específicamente diseñados para muestrear vastas zonas del océano. Estos son robots con forma de torpedo que hacen uso de su forma hidrodinámica, alas y cambios de flotabilidad para generar movimientos horizontales y verticales en la columna de agua. Un sensor que mide conductividad, temperatura y profundidad (CTD) constituye un equipamiento estándar en la plataforma. Esto se debe a que ciertas variables dinámicas del Océano se pueden derivar de la temperatura, profundidad y salinidad. Esta última se puede estimar a partir de las medidas de temperatura y conductividad. La integración de sensores CTD en planeadores submarinos no esta exenta de desafíos. Uno de ellos está relacionado con la precisión de los valores de salinidad derivados de las muestras de temperatura y conductividad. Específicamente, las estimaciones de salinidad están significativamente degradadas por el retardo térmico existente, entre la temperatura medida y la temperatura real dentro de la celda de conductividad del sensor. Esta deficiencia depende de las particularidades del flujo de entrada al sensor, su geometría y, también se ha postulado, del calor acumulado en las capas de aislamiento externo del sensor. Los efectos del retardo térmico se suelen mitigar mediante el control del flujo de entrada al sensor. Esto se obtiene generalmente mediante el bombeo de agua a través del sensor o manteniendo constante y conocida su velocidad. Aunque recientemente se han incorporado sistemas de bombeo en los CTDs a bordo de los planeadores submarinos, todavía existen plataformas equipadas con CTDs sin dichos sistemas. En estos casos, la estimación de la salinidad supone condiciones de flujo de entrada al sensor, razonablemente controladas e imperturbadas. Esta Tesis investiga el impacto, si existe, que la hidrodinámica de los planeadores submarinos pudiera tener en la eficiencia de los sensores CTD. Específicamente, se investiga primero la localización del sensor CTD (externo al fuselaje) relativa a la capa límite desarrollada a lo largo del cuerpo del planeador. Esto se lleva a cabo mediante la utilización de un modelo acoplado de fluido no viscoso con un modelo de capa límite implementado por el autor, así como mediante un programa comercial de dinámica de fluidos computacional (CFD). Los resultados indican, en ambos casos, que el sensor CTD se encuentra fuera de la capa límite, siendo las condiciones del flujo de entrada las mismas que las del flujo sin perturbar. Todavía, la velocidad del flujo de entrada al sensor CTD es la velocidad de la plataforma, la cual depende de su hidrodinámica. Por tal motivo, la investigación se ha extendido para averiguar el efecto que la velocidad de la plataforma tiene en la eficiencia del sensor CTD. Con este propósito, se ha desarrollado un modelo en elementos finitos del comportamiento hidrodinámico y térmico del flujo dentro del CTD. Los resultados numéricos indican que el retardo térmico, atribuidos originalmente a la acumulación de calor en la estructura del sensor, se debe fundamentalmente a la interacción del flujo que atraviesa la celda de conductividad con la geometría interna de la misma. Esta interacción es distinta a distintas velocidades del planeador submarino. Específicamente, a velocidades bajas del planeador (0.2 m/s), la mezcla del flujo entrante con las masas de agua remanentes en el interior de la celda, se ralentiza debido a la generación de remolinos. Se obtienen entonces desviaciones significantes entre la salinidad real y aquella estimada. En cambio, a velocidades más altas del planeador (0.4 m/s) los procesos de mezcla se incrementan debido a la turbulencia e inestabilidades. En consecuencia, la respuesta del sensor CTD es mas rápida y las estimaciones de la salinidad mas precisas que en el caso anterior. Para completar el trabajo, los resultados numéricos se han validado con pruebas experimentales. Específicamente, se ha construido un modelo a escala del sensor CTD para obtener la confirmación experimental de los modelos numéricos. Haciendo uso del principio de similaridad de la dinámica que gobierna los fluidos incompresibles, los experimentos se han realizado con flujos de aire. Esto simplifica significativamente la puesta experimental y facilita su realización en condiciones con medios limitados. Las pruebas experimentales han confirmado cualitativamente los resultados numéricos. Más aun, se sugiere en esta Tesis que la respuesta del sensor CTD mejoraría significativamente añadiendo un generador de turbulencia en localizaciones adecuadas al interno de la celda de conductividad. ABSTRACT Recent technological developments allow the transition of observational oceanography from a ship-based to a networking concept. The latter suggests that the most efficient and effective way to observe the Ocean is through a fleet of spatially distributed autonomous platforms complemented by remote sensing. Due to their maneuverability, autonomy and endurance at sea, underwater gliders are already playing a significant role in this networking observational approach. Underwater gliders were specifically designed to sample vast areas of the Ocean. These are robots with a torpedo shape that make use of their hydrodynamic shape, wings and buoyancy changes to induce horizontal and vertical motions through the water column. A sensor to measure the conductivity, temperature and depth (CTD) is a standard payload of this platform. This is because certain ocean dynamic variables can be derived from temperature, depth and salinity. The latter can be inferred from measurements of temperature and conductivity. Integrating CTD sensors in glider platforms is not exempted of challenges. One of them, concerns to the accuracy of the salinity values derived from the sampled conductivity and temperature. Specifically, salinity estimates are significantly degraded by the thermal lag response existing between the measured temperature and the real temperature inside the conductivity cell of the sensor. This deficiency depends on the particularities of the inflow to the sensor, its geometry and, it has also been hypothesized, on the heat accumulated by the sensor coating layers. The effects of thermal lag are usually mitigated by controlling the inflow conditions through the sensor. Controlling inflow conditions is usually achieved by pumping the water through the sensor or by keeping constant and known its diving speed. Although pumping systems have been recently implemented in CTD sensors on board gliders, there are still platforms with unpumped CTDs. In the latter case, salinity estimates rely on assuming reasonable controlled and unperturbed flow conditions at the CTD sensor. This Thesis investigates the impact, if any, that glider hydrodynamics may have on the performance of onboard CTDs. Specifically, the location of the CTD sensor (external to the hull) relative to the boundary layer developed along the glider fuselage, is first investigated. This is done, initially, by applying a coupled inviscid-boundary layer model developed by the author, and later by using a commercial software for computational fluid dynamics (CFD). Results indicate, in both cases, that the CTD sensor is out of the boundary layer, being its inflow conditions those of the free stream. Still, the inflow speed to the CTD sensor is the speed of the platform, which largely depends on its hydrodynamic setup. For this reason, the research has been further extended to investigate the effect of the platform speed on the performance of the CTD sensor. A finite element model of the hydrodynamic and thermal behavior of the flow inside the CTD sensor, is developed for this purpose. Numerical results suggest that the thermal lag effect is mostly due to the interaction of the flow through the conductivity cell and its geometry. This interaction is different at different speeds of the glider. Specifically, at low glider speeds (0.2 m/s), the mixing of recent and old waters inside the conductivity cell is slowed down by the generation of coherent eddy structures. Significant departures between real and estimated values of the salinity are found. Instead, mixing is enhanced by turbulence and instabilities for high glider speeds (0.4 m/s). As a result, the thermal response of the CTD sensor is faster and the salinity estimates more accurate than for the low speed case. For completeness, numerical results have been validated against model tests. Specifically, a scaled model of the CTD sensor was built to obtain experimental confirmation of the numerical results. Making use of the similarity principle of the dynamics governing incompressible fluids, experiments are carried out with air flows. This significantly simplifies the experimental setup and facilitates its realization in a limited resource condition. Model tests qualitatively confirm the numerical findings. Moreover, it is suggested in this Thesis that the response of the CTD sensor would be significantly improved by adding small turbulators at adequate locations inside the conductivity cell.

Ultra Low Power FPGA-Based Architecture for Wake-up Radio in Wireless Sensor Networks

In this paper the capabilities of ultra low power FPGAs to implement Wake-up Radios (WuR) for ultra low energy Wireless Sensor Networks (WSNs) are analyzed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the more common approaches based on ASICs or microcontrollers. In this context, energy efficiency is a key aspect, considering that usually the instant power consumption is considered a figure of merit, more than the total energy consumed by the application.

Gas sensor based on room temperature optical properties of Surface QDs

Self-organized InGaAs QDs are intensively studied for optoelectronic applications. Several approaches are in study to reach the emission wavelengths needed for these applications. The use of antimony (Sb) in either the capping layer or into the dots is one example. However, these studies are normally focused on buried QD (BQD) where there are still different controversial theories concerning the role of Sb. Ones suggest that Sb incorporates into the dot [1], while others support the hypothesis that the Sb occupies positions surrounding the dot [2] thus helping to keep their shape during the capping growth.

Wireless Sensor Network based on OCDMA for closed environments

An infrared optical wireless system is presented, consisting on autonomous remote nodes communicating with a central node. The network is designed for telecommand/telemetry purposes, comprising a large number of nodes at a low data rate. Simultaneous access is granted by using CDMA techniques, and an appropriate selection of the code family can also keep power consumption to a minimum

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.

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.

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.

Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Radio propagation modeling and measurements for ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is difficult to estimate due to the irregularity of the physical environment and affects the WSN designers? decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to build the environment database accurately, which also significantly reduces time and efforts spent on non-radio propagation issue. The 3D ray tracing is developed by using kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. Signal propagation model is proposed for the ray tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of radio. Three different WSN deployments are realized in the indoor environment of an office and the results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in pre-simulation strategy and 3D ray searching scheme and is suitable for different indoor environments.

A 0.0016 mm(2) 0.64 nJ leakage-based CMOS temperature sensor

This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes a capacitor to discharge through a transistor in the subthreshold regime. Furthermore, a novel charging mechanism for the capacitor is proposed to further increase the robustness against fabrication variability. The sensor, including digitization and interfacing, occupies 0.0016 mm2 and has an energy consumption of 47.7–633 pJ per sample. The resolution of the sensor is 0.28 °C, and the 3σ inaccuracy over the range 40–110 °C is 1.17 °C.

Liquid crystal temperature sensor based on a micrometric structure and a metallic nanometric layer

This letter presents a novel temperature sensor, which consists of an interdigitated comb electrode structure with a micrometric-scale size, nanometric metallic layer, and nematic liquid crystal (NLC) film. This sensor exploits the permittivity dependence of the NLC with temperature and principle of electrical conductivity above the percolation threshold in thin film metallic layers. The latter has been demonstrated to increase the temperature sensitivity considerably. The high impedance input reduces the power dissipation, and the high enough voltage output makes it easy to measure the output signal with high precision. The operation principle and fabrication process as well as the characterization of the temperature sensor are presented. Experimental results show that the device offers a sensitivity of 9 mV/°C and is dependent on the applied voltage. This is six times greater than the same structure without the use of a nanometric layer.

Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.