606 research outputs found

    An Application-Driven Modular IoT Architecture

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    Design of automobile panel based on ARM and Embedded Linux

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    汽车仪表是驾驶员获取汽车状态信息的关键设备,对汽车的安全行驶起着重要的作用。近年来,随着计算机、微电子和各种现场总线通信技术的广泛应用,汽车电子技术得到了迅猛的发展,汽车仪表盘上显示的信息不断增加,传统的机械式、电气式组合仪表越来越无法满足使用的需求。特别是随着汽车GPS导航、自动驾驶等新技术的日趋成熟,汽车仪表成为集显示、控制、通讯、娱乐为一体的汽车综合信息显示中心已经指日可待。 本文提出并设计了一种以ARM器件为CPU,以嵌入式Linux为操作系统的车载仪表盘系统。该仪表盘以嵌入式微处理器为核心,对汽车的各种信息状态,如电池电压、车速等参数进行采集、处理、显示和报警提示,驾驶员根据报警提...The panel of automobile is the main instrument of automobile, through which the driver can get the status of the automobile, and the safety of driving is greatly influenced by it. Recently, with the widely using of computer, micro-electronics and field bus communication technology, automobile electronical technology is developing fast, and the traditional mechanical and electrical combined instrum...学位:工学硕士院系专业:物理与机电工程学院机电工程系_精密仪器及机械学号:2005130173

    Is Europe in the Driver's Seat? The Competitiveness of the European Automotive Embedded Systems Industry

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    This report is one of a series resulting from a project entitled ¿Competitiveness by Leveraging Emerging Technologies Economically¿ (COMPLETE), carried out by JRC-IPTS. Each of the COMPLETE studies illustrates in its own right that European companies are active on many fronts of emerging and disruptive ICT technologies and are supplying the market with relevant products and services. Nevertheless, the studies also show that the creation and growth of high tech companies is still very complex and difficult in Europe, and too many economic opportunities seem to escape European initiatives and ownership. COMPLETE helps to illustrate some of the difficulties experienced in different segments of the ICT industry and by growing potential global players. This report reflects the findings of a study conducted by Egil Juliussen and Richard Robinson, two senior experts from iSuppli Corporation on the Competitiveness of the European Automotive Embedded Software industry. The report starts by introducing the market, its trends, the technologies, their characteristics and their potential economic impact, before moving to an analysis of the competitiveness of the corresponding European industry. It concludes by suggesting policy options. The research, initially based on internal expertise and literature reviews, was complemented with further desk research, expert interviews, expert workshops and company visits. The results were ultimately reviewed by experts and also in a dedicated workshop. The report concludes that currently ICT innovation in the automotive industry is a key competence in Europe, with very little ICT innovation from outside the EU finding its way into EU automotive companies. A major benefit of a strong automotive ICT industry is the resulting large and valuable employment base. But future maintenance of automotive ICT jobs within the EU will only be possible if the EU continues to have high levels of product innovation.JRC.DDG.J.4-Information Societ

    Platform-based design, test and fast verification flow for mixed-signal systems on chip

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    This research is providing methodologies to enhance the design phase from architectural space exploration and system study to verification of the whole mixed-signal system. At the beginning of the work, some innovative digital IPs have been designed to develop efficient signal conditioning for sensor systems on-chip that has been included in commercial products. After this phase, the main focus has been addressed to the creation of a re-usable and versatile test of the device after the tape-out which is close to become one of the major cost factor for ICs companies, strongly linking it to model’s test-benches to avoid re-design phases and multi-environment scenarios, producing a very effective approach to a single, fast and reliable multi-level verification environment. All these works generated different publications in scientific literature. The compound scenario concerning the development of sensor systems is presented in Chapter 1, together with an overview of the related market with a particular focus on the latest MEMS and MOEMS technology devices, and their applications in various segments. Chapter 2 introduces the state of the art for sensor interfaces: the generic sensor interface concept (based on sharing the same electronics among similar applications achieving cost saving at the expense of area and performance loss) versus the Platform Based Design methodology, which overcomes the drawbacks of the classic solution by keeping the generality at the highest design layers and customizing the platform for a target sensor achieving optimized performances. An evolution of Platform Based Design achieved by implementation into silicon of the ISIF (Intelligent Sensor InterFace) platform is therefore presented. ISIF is a highly configurable mixed-signal chip which allows designers to perform an effective design space exploration and to evaluate directly on silicon the system performances avoiding the critical and time consuming analysis required by standard platform based approach. In chapter 3 we describe the design of a smart sensor interface for conditioning next generation MOEMS. The adoption of a new, high performance and high integrated technology allow us to integrate not only a versatile platform but also a powerful ARM processor and various IPs providing the possibility to use the platform not only as a conditioning platform but also as a processing unit for the application. In this chapter a description of the various blocks is given, with a particular emphasis on the IP developed in order to grant the highest grade of flexibility with the minimum area occupation. The architectural space evaluation and the application prototyping with ISIF has enabled an effective, rapid and low risk development of a new high performance platform achieving a flexible sensor system for MEMS and MOEMS monitoring and conditioning. The platform has been design to cover very challenging test-benches, like a laser-based projector device. In this way the platform will not only be able to effectively handle the sensor but also all the system that can be built around it, reducing the needed for further electronics and resulting in an efficient test bench for the algorithm developed to drive the system. The high costs in ASIC development are mainly related to re-design phases because of missing complete top-level tests. Analog and digital parts design flows are separately verified. Starting from these considerations, in the last chapter a complete test environment for complex mixed-signal chips is presented. A semi-automatic VHDL-AMS flow to provide totally matching top-level is described and then, an evolution for fast self-checking test development for both model and real chip verification is proposed. By the introduction of a Python interface, the designer can easily perform interactive tests to cover all the features verification (e.g. calibration and trimming) into the design phase and check them all with the same environment on the real chip after the tape-out. This strategy has been tested on a consumer 3D-gyro for consumer application, in collaboration with SensorDynamics AG

    Performance assessment for mountain bike based on WSN and Cloud Technologies

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    The mountain bike is one of the most used equipment’s in outdoor sports activities. The thesis describes the design and all development and implementation of Performance Assessment for Mountain Bike based on Wireless Sensor Network (WSN) and Cloud Technologies. The work presents a distributed sensing system for cycling assessment-providing data for objective evaluation of the athlete performance during training. Thus a wireless sensor network attached to the sport equipment provides to the athlete and the coach with performance values during practice. The sensors placed in biker equipment’s behave as nodes of a WSN. This is possible with the developing of IoT-based systems in sports, the tracking and monitoring of athletes in their activities has an important role on his formation as bikers and helps to increase performance, through the analyze of each session. The implemented system performs acquisition, processing and transmission, of data using a ZigBee wireless networks that provide also machine-to-machine communication and data storage in a server located in the cloud. As in many cycling applications use the phone as a module to get the values, this work will be a little different making use of phone/tablet to consult information. The information stored on the cloud server is accessed through a mobile application that analyses and correlates all metrics calculated using the training data obtained during practice. Additional information regarding the health status may be also considered. Therefore, the system permits that athletes perform an unlimited number of trainings that can be accessed at any time through the mobile application by the bikers and coach. Based on capability of the system to save a history of the evolution of each athlete during training the system permits to perform appropriate comparisons between different training sessions and different athlete’s performances.A bicicleta de montanha é um dos equipamentos para desportos no exterior mais usada. A tese descreve todo o desenho, desenvolvimento e implementação de Performance Assessment for Mountain Bike based on WSN and Cloud Technologies. Este apresenta um sistema de deteção distribuída para o aumento do desempenho, melhorar a metodologia da prática do ciclismo e para formação de atletas. Para tal foi desenvolvida e anexada uma rede de sensores que está embutida no equipamento do ciclista, através desta rede de sensores sem fios são obtidos os valores respetivos à interação do utilizador e a sua bicicleta, sendo estes apresentados ao treinador e ao próprio ciclista. Os sensores colocados comportam-se como nós de uma rede de sensores sem fios. Isso é possível com o desenvolvimento de sistemas baseados na Internet das coisas no desporto, a observação da movimentação e monitoramento de atletas nas suas atividades tem um papel importante na sua formação como ciclistas e ajuda a aumentar o desempenho. O sistema é baseado numa rede ZigBee sem fios, que permite a comunicação máquina-para-máquina e o armazenamento de dados num servidor localizado na nuvem. Toda a informação na nuvem pode ser acedida através de uma aplicação mobile que analisa e correlaciona todos os valores calculados usando os dados recolhidos durante o treino efetuado por cada ciclista. Como em muitas aplicações de ciclismo estas usam o telefone como um módulo para obter os valores, neste trabalho o caso é diferente fazendo o uso do telefone/tablet para apenas consultar as informações. Alguma informação sobre o ciclista é fornecida para poder efetuar alguns cálculos, relativos à saúde do ciclista, neste caso toda a energia gasta na prática de um determinado treino. Toda esta informação pode ser acedida através de uma aplicação Android e por consequência num dispositivo Android. Com a aplicação desenvolvida é possível observar e processar toda a informação recolhida através dos sensores implementados, a observação dos dados recolhidos pode ser efetuada pelo treinador responsável, como pelo próprio atleta. Portanto, o sistema permite a realização de um ilimitado número de sessões de treino, estes podem ser consultados a qualquer momento através da aplicação móvel. Fazendo com que seja possível manter um histórico da evolução de cada atleta, podendo assim observar e comparar cada sessão de treino, realizada por cada atleta

    A selective dynamic compiler for embedded Java virtual machine targeting ARM processors

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    Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2004-2005Ce travail présente une nouvelle technique de compilation dynamique sélective pour les systèmes embarqués avec processeurs ARM. Ce compilateur a été intégré dans la plateforme J2ME/CLDC (Java 2 Micro Edition for Connected Limited Device Con- figuration). L’objectif principal de notre travail est d’obtenir une machine virtuelle accélérée, légère et compacte prête pour l’exécution sur les systèmes embarqués. Cela est atteint par l’implémentation d’un compilateur dynamique sélectif pour l’architecture ARM dans la Kilo machine virtuelle de Sun (KVM). Ce compilateur est appelé Armed E-Bunny. Premièrement, on présente la plateforme Java, le Java 2 Micro Edition(J2ME) pour les systèmes embarqués et les composants de la machine virtuelle Java. Ensuite, on discute les différentes techniques d’accélération pour la machine virtuelle Java et on détaille le principe de la compilation dynamique. Enfin, on illustre l’architecture, le design (la conception), l’implémentation et les résultats expérimentaux de notre compilateur dynamique sélective Armed E-Bunny. La version modifiée de KVM a été portée sur un ordinateur de poche (PDA) et a été testée en utilisant un benchmark standard de J2ME. Les résultats expérimentaux de la performance montrent une accélération de 360 % par rapport à la dernière version de la KVM de Sun avec un espace mémoire additionnel qui n’excède pas 119 kilobytes.This work presents a new selective dynamic compilation technique targeting ARM 16/32-bit embedded system processors. This compiler is built inside the J2ME/CLDC (Java 2 Micro Edition for Connected Limited Device Configuration) platform. The primary objective of our work is to come up with an efficient, lightweight and low-footprint accelerated Java virtual machine ready to be executed on embedded machines. This is achieved by implementing a selective ARM dynamic compiler called Armed E-Bunny into Sun’s Kilobyte Virtual Machine (KVM). We first present the Java platform, Java 2 Micro Edition (J2ME) for embedded systems and Java virtual machine components. Then, we discuss the different acceleration techniques for Java virtual machine and we detail the principle of dynamic compilation. After that we illustrate the architecture, design, implementation and experimental results of our selective dynamic compiler Armed E-Bunny. The modified KVM is ported on a handheld PDA and is tested using standard J2ME benchmarks. The experimental results on its performance demonstrate that a speedup of 360% over the last version of Sun’s KVM is accomplished with a footprint overhead that does not exceed 119 kilobytes

    Exploration of Deep Learning Applications on an Autonomous Embedded Platform (Bluebox 2.0)

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    Indiana University-Purdue University Indianapolis (IUPUI)An Autonomous vehicle depends on the combination of latest technology or the ADAS safety features such as Adaptive cruise control (ACC), Autonomous Emergency Braking (AEB), Automatic Parking, Blind Spot Monitor, Forward Collision Warning or Avoidance (FCW or FCA), Lane Departure Warning. The current trend follows incorporation of these technologies using the Artificial neural network or Deep neural network, as an imitation of the traditionally used algorithms. Recent research in the field of deep learning and development of competent processors for autonomous or self-driving car have shown amplitude of prospect, but there are many complexities for hardware deployment because of limited resources such as memory, computational power, and energy. Deployment of several mentioned ADAS safety feature using multiple sensors and individual processors, increases the integration complexity and also results in the distribution of the system, which is very pivotal for autonomous vehicles. This thesis attempts to tackle two important adas safety feature: Forward collision Warning, and Object Detection using the machine learning and Deep Neural Networks and there deployment in the autonomous embedded platform. 1. A machine learning based approach for the forward collision warning system in an autonomous vehicle. 2. 3-D object detection using Lidar and Camera which is primarily based on Lidar Point Clouds. The proposed forward collision warning model is based on the forward facing automotive radar providing the sensed input values such as acceleration, velocity and separation distance to a classifier algorithm which on the basis of supervised learning model, alerts the driver of possible collision. Decision Tress, Linear Regression, Support Vector Machine, Stochastic Gradient Descent, and a Fully Connected Neural Network is used for the prediction purpose. The second proposed methods uses object detection architecture, which combines the 2D object detectors and a contemporary 3D deep learning techniques. For this approach, the 2D object detectors is used first, which proposes a 2D bounding box on the images or video frames. Additionally a 3D object detection technique is used where the point clouds are instance segmented and based on raw point clouds density a 3D bounding box is predicted across the previously segmented objects

    Advanced Strategies for Robot Manipulators

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    Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored
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