Design of a Wireless Vision Sensor for Object Tracking in Wireless Vision Sensor Networks

The integration of CMOS cameras with embedded processors and wireless communication devices has enabled the development of distributed wireless vision systems. Wireless Vision Sensor Networks (WVSNs), which consist of wirelessly connected embedded systems with vision and sensing capabilities, provide wide variety of application areas that have not been possible to realize with the wall-powered vision systems with wired links or scalar-data based wireless sensor networks. In this paper, the design of a middleware for a wireless vision sensor node is presented for the realization of WVSNs. The implemented wireless vision sensor node is tested through a simple vision application to study and analyze its capabilities, and determine the challenges in distributed vision applications through a wireless network of low-power embedded devices. The results of this paper highlight the practical concerns for the development of efficient image processing and communication solutions for WVSNs and emphasize the need for cross-layer solutions that unify these two so-far-independent research areas.

Pervasive Sensing in Future Networks

Pervasive Sensing is a recent research trend that aims at providing widespread computing and sensing capabilities to enable the creation of smart environments that can sense, process, and act by considering input coming from both people and devices. The capabilities necessary for Pervasive Sensing are nowadays available on a plethora of devices, from embedded devices to PCs and smartphones. The wide availability of new devices and the large amount of data they can access enable a wide range of novel services in different areas, spanning from simple data collection systems to socially-aware collaborative filtering. However, the strong heterogeneity and unreliability of devices and sensors poses significant challenges. So far, existing works on Pervasive Sensing have focused only on limited portions of the whole stack of available devices and data that they can use, to propose and develop mainly vertical solutions. The push from academia and industry for this kind of services shows that time is mature for a more general support framework for Pervasive Sensing solutions able to enhance frail architectures, promote a well balanced usage of resources on different devices, and enable the widest possible access to sensed data, while ensuring a minimal energy consumption on battery-operated devices. This thesis focuses on pervasive sensing systems to extract design guidelines as foundation of a comprehensive reference model for multi-tier Pervasive Sensing applications. The validity of the proposed model is tested in five different scenarios that present peculiar and different requirements, and different hardware and sensors. The ease of mapping from the proposed logical model to the real implementations and the positive performance result campaigns prove the quality of the proposed approach and offer a reliable reference model, together with a direction for the design and deployment of future Pervasive Sensing applications.

Technologies for Ambient intelligence: from Smart Objects to Sensor Networks

n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.

A Development Methodology to Facilitate the Integration of Smart Spaces into the Web of Things

How to create or integrate large Smart Spaces (considered as mash-ups of sensors and actuators) into the paradigm of ?Web of Things? has been the motivation of many recent works. A cutting-edge approach deals with developing and deploying web-enabled embedded devices with two major objectives: 1) to integrate sensor and actuator technologies into everyday objects, and 2) to allow a diversity of devices to plug to Internet. Currently, developers who want to use this Internet-oriented approach need have solid understanding about sensorial platforms and semantic technologies. In this paper we propose a Resource-Oriented and Ontology-Driven Development (ROOD) methodology, based on Model Driven Architecture (MDA), to facilitate to any developer the development and deployment of Smart Spaces. Early evaluations of the ROOD methodology have been successfully accomplished through a partial deployment of a Smart Hotel.

Desarrollo de aplicaciones de comunicaciones inalámbricas en sistemas de monitorización estructural desarrollados en aeronáutica.

Los Sistemas de SHM o de monitorización de la integridad estructural surgen ante la necesidad de mejorar los métodos de evaluación y de test no destructivos convencionales. De esta manera, se puede tener controlado todo tipo de estructuras en las cuales su correcto estado o funcionamiento suponga un factor crítico. Un Sistema SHM permite analizar una estructura concreta capturando de manera periódica el estado de la integridad estructural, que en este proyecto se ha aplicado a estructuras aeronáuticas. P.A.M.E.L.A. (Phase Array Monitoring for Enhanced Life Assessment) es la denominación utilizada para definir una serie de equipos electrónicos para Sistemas SHM desarrollados por AERNOVA y los Grupos de Diseño Electrónico de las universidades UPV/EHU y UPM. Los dispositivos P.A.M.E.L.A. originalmente no cuentan con tecnología Wi-Fi, por lo que incorporan un módulo hardware independiente que se encarga de las comunicaciones inalámbricas, a los que se les denomina Nodos. Estos Nodos poseen un Sistema Operativo propio y todo lo necesario para administrar y organizar la red Mallada Wi-Fi. De esta manera se obtiene una red mallada inalámbrica compuesta por Nodos que interconectan los Sistemas SHM y que se encargan de transmitir los datos a los equipos que procesan los resultados adquiridos por P.A.M.E.L.A. Los Nodos son dispositivos empotrados que llevan instalados un firmware basado en una distribución de Linux para Nodos (o Routers), llamado Openwrt. Que para disponer de una red mallada necesitan de un protocolo orientado a este tipo de redes. Entre las opciones de protocolo más destacadas se puede mencionar: DSDV (Destination Sequenced Distance Vector), OLSR (Optimized Link State Routing), B.A.T.M.A.N-Adv (Better Approach To Mobile Adhoc Networking Advance), BMX (una versión de B.A.T.M.A.N-Adv), AODV (Ad hoc On-Demand Distance Vector) y el DSR (Dynamic Source Routing). Además de la existencia de protocolos orientados a las redes malladas, también hay organizaciones que se dedican a desarrollar firmware que los utilizan, como es el caso del firmware llamado Nightwing que utiliza BMX, Freifunk que utiliza OLSR o Potato Mesh que utiliza B.A.T.M.A.N-Adv. La ventaja de estos tres firmwares mencionados es que las agrupaciones que las desarrollan proporcionan las imágenes precompiladas del sistema,listas para cargarlas en distintos modelos de Nodos. En este proyecto se han instalado las imágenes en los Nodos y se han probado los protocolos BMX, OLSR y B.A.T.M.A.N.-Adv. Concluyendo que la red gestionada por B.A.T.M.A.N.-Adv era la que mejor rendimiento obtenía en cuanto a estabilidad y ancho de banda. Después de haber definido el protocolo a usar, se procedió a desarrollar una distribución basada en Openwrt, que utilice B.A.T.M.A.N.-Adv para crear la red mallada, pero que se ajuste mejor a las necesidades del proyecto, ya que Nightwing, Freifunk y Potato Mesh no lo hacían. Además se implementan aplicaciones en lenguaje ANSI C y en LabVIEW para interactuar con los Nodos y los Sistemas SHM. También se procede a hacer alguna modificación en el Hardware de P.A.M.E.L.A. y del Nodo para obtener una mejor integración entre los dos dispositivos. Y por ultimo, se prueba la transferencia de datos de los Nodos en distintos escenarios. ABSTRACT. Structural Health Monitoring (SHM) systems arise from the need of improving assessment methods and conventional nondestructive tests. Critical structures can be monitored using SHM. A SHM system analyzes periodically a specific structure capturing the state of structural integrity. The aim of this project is to contribute in the implementation of Mesh network for SHM system in aircraft structures. P.A.M.E.L.A. (Phase Array Monitoring for Enhanced Life Assessment) is the name for electronic equipment developed by AERNOVA, the Electronic Design Groups of university UPV/EHU and the Instrumentation and Applied Acoustics research group from UPM. P.A.M.E.L.A. devices were not originally equipped with Wi-Fi interface. In this project a separate hardware module that handles wireless communications (nodes) has been added. The nodes include an operating system for manage the Wi-Fi Mesh Network and they form the wireless mesh network to link SHM systems with monitoring equipment. Nodes are embedded devices with an installed firmware based on special Linux distribution used in routers or nodes, called OpenWRT. They need a Mesh Protocol to stablish the network. The most common protocols options are: DSDV (Destination Sequenced Distance Vector), OLSR (Optimized Link State Routing), BATMAN-Adv (Better Approach To Mobile Ad-hoc Networking Advance), BMX (a version of BATMAN-Adv) AODV (Ad hoc on-Demand Distance Vector) and DSR (Dynamic Source Routing). In addition, there are organizations that are dedicated to develope firmware using these Mesh Protocols, for instance: Nightwing uses BMX, Freifunk use OLSR and Potato Mesh uses BATMAN-Adv. The advantage of these three firmwares is that these groups develop pre-compiled images of the system ready to be loaded in several models of Nodes. In this project the images were installed in the nodes. In this way, BMX, OLSR and BATMAN-Adv have been tested. We conclude that the protocol BATMAN-Adv has better performance in terms of stability and bandwidth. After choosing the protocol, the objective was to develop a distribution based on OpenWRT, using BATMAN-Adv to create the mesh network. This distribution is fitted to the requirements of this project. Besides, in this project it has been developed applications in C language and LabVIEW to interact with the Nodes and the SHM systems. The project also address some modifications to the PAMELA hardware and the Node, for better integration between both elements. Finally, data transfer tests among the different nodes in different scenarios has been carried out.

On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework

The astonishing development of diverse and different hardware platforms is twofold: on one side, the challenge for the exascale performance for big data processing and management; on the other side, the mobile and embedded devices for data collection and human machine interaction. This drove to a highly hierarchical evolution of programming models. GVirtuS is the general virtualization system developed in 2009 and firstly introduced in 2010 enabling a completely transparent layer among GPUs and VMs. This paper shows the latest achievements and developments of GVirtuS, now supporting CUDA 6.5, memory management and scheduling. Thanks to the new and improved remoting capabilities, GVirtus now enables GPU sharing among physical and virtual machines based on x86 and ARM CPUs on local workstations,computing clusters and distributed cloud appliances.

Street lighting mesh network protocol

The digital revolution of the 21st century contributed to stem the Internet of Things (IoT). Trillions of embedded devices using the Internet Protocol (IP), also called smart objects, will be an integral part of the Internet. In order to support such an extremely large address space, a new Internet Protocol, called Internet Protocol Version 6 (IPv6) is being adopted. The IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) has accelerated the integration of WSNs into the Internet. At the same time, the Constrained Application Protocol (CoAP) has made it possible to provide resource constrained devices with RESTful Web services functionalities. This work builds upon previous experience in street lighting networks, for which a proprietary protocol, devised by the Lighting Living Lab, was implemented and used for several years. The proprietary protocol runs on a broad range of lighting control boards. In order to support heterogeneous applications with more demanding communication requirements and to improve the application development process, it was decided to port the Contiki OS to the four channel LED driver (4LD) board from Globaltronic. This thesis describes the work done to adapt the Contiki OS to support the Microchip TM PIC24FJ128GA308 microprocessor and presents an IP based solution to integrate sensors and actuators in smart lighting applications. Besides detailing the system’s architecture and implementation, this thesis presents multiple results showing that the performance of CoAP based resource retrievals in constrained nodes is adequate for supporting networking services in street lighting networks.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.

Perceiving the 3d world from single images

Depth represents a crucial piece of information in many practical applications, such as obstacle avoidance and environment mapping. This information can be provided either by active sensors, such as LiDARs, or by passive devices like cameras. A popular passive device is the binocular rig, which allows triangulating the depth of the scene through two synchronized and aligned cameras. However, many devices that are already available in several infrastructures are monocular passive sensors, such as most of the surveillance cameras. The intrinsic ambiguity of the problem makes monocular depth estimation a challenging task. Nevertheless, the recent progress of deep learning strategies is paving the way towards a new class of algorithms able to handle this complexity. This work addresses many relevant topics related to the monocular depth estimation problem. It presents networks capable of predicting accurate depth values even on embedded devices and without the need of expensive ground-truth labels at training time. Moreover, it introduces strategies to estimate the uncertainty of these models, and it shows that monocular networks can easily generate training labels for different tasks at scale. Finally, it evaluates off-the-shelf monocular depth predictors for the relevant use case of social distance monitoring, and shows how this technology allows to overcome already existing strategies limitations.

A parallel convolutional coder including embedded puncturing with application to consumer devices

As consumers demand more functionality) from their electronic devices and manufacturers supply the demand then electrical power and clock requirements tend to increase, however reassessing system architecture can fortunately lead to suitable counter reductions. To maintain low clock rates and therefore reduce electrical power, this paper presents a parallel convolutional coder for the transmit side in many wireless consumer devices. The coder accepts a parallel data input and directly computes punctured convolutional codes without the need for a separate puncturing operation while the coded bits are available at the output of the coder in a parallel fashion. Also as the computation is in parallel then the coder can be clocked at 7 times slower than the conventional shift-register based convolutional coder (using DVB 7/8 rate). The presented coder is directly relevant to the design of modern low-power consumer devices

Energy harvesting from piezoelectric devices embedded in a 3D printed wing

This thesis work has been carried out at Clarkson University in Potsdam NY, USA and involved the design of a low elongation wing, consisting of parts made by polylactide (PLA) using the fused deposition model (FDM) technology of Rapid Prototyping, then assembled together in a thin aluminum spar. The aim of the research is to evaluate the feasibility of collecting electrical energy by converting mechanical energy from the vibration of the wing flutter. With this aim piezoelectric stripes were glued in the inner part of the wing, as well as on the aluminum spar, as monomorphic configuration. During the phases of the project, particular attention was given to the geometry and the materials used, in order to trigger the flutter for low flow velocity. The CAD software SolidWorks® was used for the design of the wing and then the drawings were sent to the Clarkson machine shop in order to to produce the parts required by the wing assembly. FEM simulations were performed, using software MSC NASTRAN/PATRAN®, to evaluate the stiffness of the whole wing as well as the natural vibration modes of the structure. These data, in a first approximation, were used to predict the flutter speed. Finally, experimental tests in the Clarkson wind tunnel facility were carried out in order to validate the results obtained from FEM analysis. The power collected by the piezoelectrics under flutter condition was addressed by tuning the resistors downstream the electronic circuit of the piezoelectrics.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Reconfigurable SiC Embedded Photonic Structures with Self Optical Bias Control

Multilayered heterostructures based on embedded a-Si:H and a-SiC:H p-i-n filters are analyzed from differential voltage design perspective using short- and long-pass filters. The transfer functions characteristics are presented. A numerical simulation is presented to explain the filtering properties of the photonic devices. Several monochromatic pulsed lights, separately (input channels) or in a polychromatic mixture (multiplexed signal) at different bit rates, illuminated the device. Steady-state optical bias is superimposed from the front and the back side. Results show that depending on the wavelength of the external background and impinging side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. Particular attention is given to the amplification coefficient weights, which allow to take into account the wavelength background effects when a band or frequency needs to be filtered or the gate switch, in which optical active filter gates are used to select and filter input signals to specific output ports in wavelength division multiplexing (WDM) communication systems. This nonlinearity provides the possibility for selective removal or addition of wavelengths. A truth table of an encoder that performs 8-to-1 MUX function exemplifies the optoelectronic conversion.

A biosignal embedded system for physiological computing

Thesis submitted in the fulfilment of the requirements for the Degree of Master in Electronic and Telecomunications Engineering