Current Issue : July - September Volume : 2015 Issue Number : 3 Articles : 4 Articles
Internet-of-Things (IoT) is the convergence of Internet with RFID, Sensor and smart objects. IoT can be defined as “things belonging to the Internet” to supply and access all of real-world information. Billions of devices are expected to be associated into the system and that shall require huge distribution of networks as well as the process of transforming raw data into meaningful inferences. IoT is the biggest promise of the technology today, but still lacking a novel mechanism, which can be perceived through the lenses of Internet, things and semantic vision. Internet of Things is a new type of Internet application which makes the thing’s information be shared on a global scale. Internet of Things has two attributes: being an Internet application and dealing with thing’s information and four differential features: only for thing’s information, coded by UID or EPC, stored in RFID electronic tag, uploaded by non-contact reading with RFID reader. The descriptive models for Internet of Things are introduced based on the basic attributes and the differential features.The Internet is continuously changing and evolving. The main communication form of present Internet is human-human. The Internet of Things (IoT) can be considered as the future evaluation of the Internet that realizes machine-to-machine (M2M) learning. Thus, IoT provides connectivity for everyone and everything. The IoT embeds some intelligence in Internet connected objects to communicate, exchange information, take decisions, invoke actions and provide amazing services. The IoT is getting increasing popularity for academia, industry as well as government that has the potential to bring significant personal, professional and economic benefits....
This paper addresses the design of embedded systems for outdoor augmented reality (AR) applications integrated to\nsee-through glasses. The set of tasks includes object positioning, graphic computation, as well as wireless\ncommunications, and we consider constraints such as real-time, low power, and low footprint. We introduce an\noriginal sailor assistance application, as a typical, useful, and complex outdoor AR application, where\ncontext-dependent virtual objects must be placed in the user field of view according to head motions and ambient\ninformation. Our study demonstrates that it is worth working on power optimization, since the embedded system\nbased on a standard general-purpose processor (GPP) + graphics processing unit (GPU) consumes more than\nhigh-luminosity see-through glasses. This work presents then three main contributions, the first one is the choice and\ncombinations of position and attitude algorithms that fit with the application context. The second one is the\narchitecture of the embedded system, where it is introduced as a fast and simple object processor (OP) optimized for\nthe domain of mobile AR. Finally, the OP implements a new pixel rendering method (incremental pixel shader (IPS)),\nwhich is implemented in hardware and takes full advantage of Open GL ES light model. A GP+OP(s) complete\narchitecture is described and prototyped on field programmable gate-array (FPGA). It includes hardware/software\npartitioning based on the analysis of application requirements and ergonomics....
Future Driving Assistance Systems (DAS) will have to react to changes within\nthe system at runtime. This might be the case in Car-to-X systems where the availability of\ncommunication partners changes dynamically. Another example are systems like DAS for\ntruck and trailer combinations where a trailer might be disconnected and replaced by another\none several times a day. State-of-the-art DAS are not capable of handling these runtime\nchanges. In our approach we make usage of the principles of Service-orientation to generate\nself-adaptive DAS on architectural level. But this technical approach requires the definition\nof a development process that fits into the practices within the automotive industry. This\npaper introduces SOMA4DDAS, a model-based development process based on the UML\nprofile SoaML. SOMA4DDAS describes a tri-phase procedure to transfer an idea for a DAS\ninto a detailed specification of the application and the Services involved. These phases are\nintegrated into the ââ?¬Å?core process for system and software developmentââ?¬Â (CPSSD), a standard\nprocess within the automotive industry. The paper illustrates the benefits of this approach by\ndeveloping a truck and trailer DAS consisting of 13 different Services....
The widespread adoption of wireless systems for industrial automation calls for\nthe development of efficient tools for virtual planning of network deployments similarly\nas done for conventional Fieldbus and wired systems. In industrial sites the radio signal\npropagation is subject to blockage due to highly dense metallic structures. Network planning\nshould therefore account for the number and the density of the 3D obstructions surrounding\neach link. In this paper we address the problem of wireless node deployment in wireless\nindustrial networks, with special focus on WirelessHART IEC 62591 and ISA SP100 IEC\n62734 standards. The goal is to optimize the network connectivity and develop an effective\ntool that can work in complex industrial sites characterized by severe obstructions. The\nproposed node deployment approach is validated through a case study in an oil refinery\nenvironment. It includes an ad-hoc simulation environment (RFSim tool) that implements\nthe proposed network planning approach using 2D models of the plant, providing connectivity\ninformation based on user-defined deployment configurations. Simulation results obtained\nusing the proposed simulation environment were validated by on-site measurements....
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