Embedded Hardware Architecture Research Articles

Efficient Embedded Hardware Architecture for Stabilised Tracking Sighting System of Armoured Fighting Vehicles

A line-of-sight stabilised sighting system, capable of target tracking and video stabilisation is a prime requirement of any armoured fighting tank vehicle for military surveillance and weapon firing. Typically, such sighting systems have three prime electro-optical sensors i.e. day camera for viewing in day conditions, thermal camera for night viewing and eye-safe laser range finder for obtaining the target range. For laser guided missile firing, additional laser target designator may be a part of sighting system. This sighting system provides necessary parameters for the fire control computer to compute ballistic offsets to fire conventional ammunition or fire missile. System demands simultaneous interactions with electro-optical sensors, servo sensors, actuators, multi-function display for man-machine interface, fire control computer, logic controller and other sub-systems of tank. Therefore, a complex embedded electronics hardware is needed to respond in real time for such system. An efficient electronics embedded hardware architecture is presented here for the development of this type of sighting system. This hardware has been developed around SHARC 21369 processor and FPGA. A performance evaluation scheme is also presented for this sighting system based on the developed hardware.

One-dimensional filtering based two-bit transform and its efficient hardware architecture for fast motion estimation

Video encoding is one of the most emerging application in many consumer electronics devices such as smartphones, tablets, cameras and camcorders in order to reduce required memory size for recording and utilized bandwidth for transmission purposes. The processing and battery power required for real-time video encoding is an important challenge for this kind of devices. Thus, efficient video encoding hardware architectures are required. Motion estimation process consumes most of the resources in a typical video encoder. Hence, low-complexity motion estimation approaches with efficient hardware implementations are investigated in the literature. In this paper, a novel low-complexity motion estimation approach based on one-dimensional filtering of input frames to construct two bit-planes for matching is presented. An embedded hardware architecture is also presented in order to demonstrate feasibility of the seamless integration into the state of the art consumer electronics devices. The, binarization stage of filtering based low- complexity motion estimation approaches are implemented in hardware first time in the literature. Experimental results show that the proposed motion estimation method and its hardware architecture provides an efficient alternative to existing low-complexity ME methods.

Street Viewer: An Autonomous Vision Based Traffic Tracking System.

The development of intelligent transportation systems requires the availability of both accurate traffic information in real time and a cost-effective solution. In this paper, we describe Street Viewer, a system capable of analyzing the traffic behavior in different scenarios from images taken with an off-the-shelf optical camera. Street Viewer operates in real time on embedded hardware architectures with limited computational resources. The system features a pipelined architecture that, on one side, allows one to exploit multi-threading intensively and, on the other side, allows one to improve the overall accuracy and robustness of the system, since each layer is aimed at refining for the following layers the information it receives as input. Another relevant feature of our approach is that it is self-adaptive. During an initial setup, the application runs in learning mode to build a model of the flow patterns in the observed area. Once the model is stable, the system switches to the on-line mode where the flow model is used to count vehicles traveling on each lane and to produce a traffic information summary. If changes in the flow model are detected, the system switches back autonomously to the learning mode. The accuracy and the robustness of the system are analyzed in the paper through experimental results obtained on several different scenarios and running the system for long periods of time.

Operating System from the Scratch: A Problem-based Learning Approach for the Emerging Demands on OS Development

In recent past history of computer systems industry, for decades, the hegemony of a few de facto standards dictated by major proprietary commercial products dominated the Operating Systems (OS) field. In such technological context, conso- nantly to this trend, the knowledge objective focused by academical and training courses on OS-related disciplines has often been addressed more from the stand point of essential theoretical background than of the technical skills for actuation on de- sign and development field. Emerging paradigms, nevertheless, have been rapidly changing this scenario. Among them, the establishment of Open Source concept is boosting the growing diversity of new operating systems; concomitantly, evolution of embedded hardware architectures has make it possible to run sophisticated operating systems where only bare rudimentary, ad hoc system-software were once practical. Aligned along this perspective, this paper introduces a new platform for teaching and training programs on OS development founded on a project-based approach which guides the student throughout the process of designing and programming a sufficiently simple, but yet realistic and fully functional, OS from the scratch. The differential of the present proposal regarding related works is that, instead of either merely inspecting example-code or experimenting with simulators, the apprentice is guided across the challenge of coding an entire new instance of a didactic system specification. A comparison of the companion OS-example with existing alternatives brings out a less complex implementation structure which maps conceptual modules with implementation blocks in an intuitive correspondence and with reduced function cou- pling. Moreover, the learning platform comes with a courseware material consistently linked to the laboratory practices, and aimed at the systemic comprehension of the many related multidisciplinary aspects.

Wireless Network Security Architecture with Blowfish Encryption Model

In this research paper ,we developed a model for a large network, wireless nodes are interconnected and each can be considered as a node processor that offer services to other node processors connected to a specific network. A very high proportion of the nodes that offer services need to carry out an authentication process so as to make an access request to the node offering the service. In this context, an integrated reconfigurable network security architecture moved to the application layer has become the need of the day for secure wireless data sharing. The security schemes of the seven layer OSI architecture need to be placed intrinsically in the wireless node itself and should be capable of supporting the MAC layer, IP address based layer and the routing protocols of the network layer. This work focuses on the use of emulator and embedded hardware architectures for wireless network security. In this work, the individual nodes can have a unique security signature pattern maintained by respective wireless nodes using an encryption algorithm and this is made dynamic. The metrics includes latency, throughput, Scalability, Effects of data transfer operation

Performance analysis of massively parallel embedded hardware architectures for retinal image processing

This paper examines the implementation of a retinal vessel tree extraction technique on different hardware platforms and architectures. Retinal vessel tree extraction is a representative application of those found in the domain of medical image processing. The low signal-to-noise ratio of the images leads to a large amount of low-level tasks in order to meet the accuracy requirements. In some applications, this might compromise computing speed. This paper is focused on the assessment of the performance of a retinal vessel tree extraction method on different hardware platforms. In particular, the retinal vessel tree extraction method is mapped onto a massively parallel SIMD (MP-SIMD) chip, a massively parallel processor array (MPPA) and onto an field-programmable gate arrays (FPGA).

Hands-on oriented curriculum and laboratory development for embedded system design

As embedded systems are getting popular in industrial product designs, a dedicated teaching laboratory for embedded systems (EST Lab) has been setup for college and graduate students to get familiar with embedded system engineering and researches. In this paper, we present our experiences in embedded system education curriculum and teaching laboratory design carried out in the past few years. Accompanied by a series of courses with hands-on exercises, students can understand the whole picture of embedded systems in a more systematic way. To give students a comprehensive view of embedded systems, the curriculum includes not only embedded hardware architectures and operating systems but also embedded user-level software designs. We select the most popular and available open-source operating system, Linux 2.6, as the primary experimental platform for all laboratory practices. In addition to the course design, several research results derived from this laboratory are also presented in this paper.