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检索条件"任意字段=11th International Conference on Embedded and Real-Time Computing Systems and Applications"

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Hard real-time Capable OPC UA Server as Hardware Peripheral for Single Chip IoT systems 24

Hard Real-Time Capable OPC UA Server as Hardware Peripheral ...

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24th IEEE international conference on Emerging Technologies and Factory Automation (ETFA)

作者： Iatrou, Chris Paul Bauer, Heiner Graube, Markus Hoppner, Sebastian Rahm, Julian Urbas, Leon Tech Univ Dresden Chair Proc Control & Syst Engn Dresden Germany Tech Univ Dresden Chai Highly Parallel VLSI Syst & Neuromicroelect Dresden Germany

ISBN: (纸本)9781728103037

the fast semantics project examines the use of the OPC Unified Architecture (OPC UA) in embedded industrial systems and proposes the design of a customizable, hard real time capable OPC UA Intellectual Property Core (IP Core) for single chip computing plattforms. this allows using OPC UA in both novel energy efficient sensor applications and in state of the art field devices. these single chip OPC UA servers form the semantic data sources for future applications such as cloud based added value services or machine learning applications. this article presents the design alternatives and first synthesis results for the implementation of OPC UA servers in embedded systems.

关键词： opc ua process automation iot system on chip soc fpga asic intellectual property core ip core

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A study on Cloud enabled applications and their Security Issues

A study on Cloud enabled Applications and their Security Iss...

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international conference on computing and Networking Technology (ICCNT)

作者： Vidhi Mody Vrushti Mody Soham Parekh B.Tech. Computer Engineering Mukesh Patel School of Technology Management and Engineering NMIMS B.E. Computer Engineering Dwarkadas Jivanlal Sanghvi College of Engineering

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Cloud computing was first established to connect people and data at anytime from anywhere in the 1960s. Today cloud computing is one of the most widely used technologies. Its applications include Multi-cloud, healthcare, testing, finance, data storage and handling big data to increase efficiency and how it differs from traditional systems. We have stated how cloud computing can be used in various domains and have compared its efficiency to traditional systems in terms of data recovery, access control, management, security and cost. However, like any other technology, this one too might have flaws which can be exploited. this paper also lists the security challenges that will have to be kept in mind while implementing these systems.

关键词： Cloud computing Security Medical services real-time systems Maintenance engineering Data privacy Computational modeling

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A Detailed Investigation on embedded computing systems for IoT applications

A Detailed Investigation on Embedded Computing Systems for I...

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international conference on Advanced computing and Communication systems (ICACCS)

作者： M. Ashwini Renjith V. Ravi MEA Engineering College Malappuram Kerala India

ISBN: (数字)9781728151977

ISBN: (纸本)9781728151984

the Internet of things(IoT) is a revolutionary paradigm in Information technology. IoT interconnects the various objects to internet thus being considered as virtual objects. It is considered that the IoT is the next big `thing' in internet. Internet uses the Internet protocol suite (IP/TCP) by which computer networks are interconnected in order to serve the users worldwide. thus billions of objects which would be provided with a unique identifiers(UID's), will be outfitted using several actuators and sensors and connecting those to internet which can be accessed using technologies like real time services, RFID, embedded sensing etc. IoT aims at improving the quality of human life. It is necessary to transform the cities by improving transportation systems, infrastructure, providing waste management etc. Currently as the internet infrastructure is almost available everywhere, thus the embedded computing device can be exposed to the internet influence. Hence the real-time data can be analyzed and used to create desired outcomes. IoT has wide range of applications like Smart cities, Industrial automation, Smart home applications, healthcare, wearables, agriculture etc.

关键词： Hardware Field programmable gate arrays Internet of things Clocks Universal Serial Bus Sensors Pins

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Toward real-time object detection on heterogeneous embedded systems 9

Toward real-time object detection on heterogeneous embedded ...

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9th international conference on Computer and Knowledge Engineering (ICCKE)

作者： Niazi-Razavi, Milad Savadi, Abdorreza Noori, Hamid Ferdowsi Univ Mashhad Mashhad Razavi Khorasan Iran

ISBN: (纸本)9781728150758

low power consumption and high efficiency of heterogeneous systems improves processing power and enables the implementation of real-time applications. Deep learning, as one of the hottest topics of today, plays an important role in solving difficult problems such as machine vision. the use of traditional methods for solving visual machine problems requires the engineering of features by humans, which makes it difficult to create a comprehensive model for a problem. the use of revolutionary deep learning in the machine vision, which along with the embedded systems can be useful in many today's issues. Convolutional neural networks have shown a high degree of efficiency in the task of categorizing images and detecting objects. An important feature in neural networks is the intrinsic parallelism of its structure, which results in the use of embedded heterogeneous systems that can provide excellent performance in the implementation of neural networks. Implementing real-time objects detection systems in enclosed environments with limited computing resources and memory is challenging. this paper presents a method for implementing the MobileNet-SSD object detection system on the Jetson TK1, which attempts to improve performance by changing the network's convoys and dividing tasks between the central and the graphics processor.

关键词： Object Detection embedded System realtime Nvidia Jetson Heterogeneous System MobileNet SSD

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IoT Monitoring of Water Consumption for Irrigation systems Using SEMMA Methodology 11th

IoT Monitoring of Water Consumption for Irrigation Systems U...

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11th international conference on ntelligent Human Computer Interaction (IHCI)

作者： Lopez-Torres, Sandra Lopez-Torres, Humberto Rocha-Rocha, Jimmy Aziz Butt, Shariq Imran Tariq, Muhammad Collazos-Morales, Carlos Pineres-Espitia, Gabriel Univ Costa Barranquilla 080002 Colombia Inst Tecnol Soledad Atlantico ITSA Barranquilla 080002 Colombia Univ Lahore Islamabad 54590 Pakistan Super Univ Lahore Lahore 53770 Pakistan Univ Manuela Beltran Bogota 111321 Colombia

ISBN: (纸本)9783030446895;9783030446888

the efficient use of water is an issue that has captured the attention of scientists, technicians, and the community at large. the sustainability of water resources has been threatened by the current imbalance between water supply and demand. Intelligent consumption of water would contribute to the balance and reduce the waste in applications such as the agriculture. this paper shows the design of a water consumption monitoring system based on the Internet of things (IoT). With the implementation of this system could be known in real time the consumption of water in a crop. In addition, the user of the system may take corrective actions that optimize their water consumption;this is achieved by applying the SEMMA methodology to evaluate the data obtained by the system using two cluster algorithms, Simple K-means and GenClus++. With the application of SEMMA it was possible to determine periods of water consumption that were considered as waste in the irrigation of crops, applying data analysis with both algorithms.

关键词： Internet of things (IoT) Irrigation system Sample Explore Modify Model, and Assess (SEMMA) Water consumption

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Citizen weather stations data for monitoring applications and urban climate research: An example of Moscow megacity 11

Citizen weather stations data for monitoring applications an...

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11th international conference and Early Career Scientists School on Environmental Observations, Modeling and Information systems, ENVIROMIS 2020

作者： Varentsov, M.I. Samsonov, T.E. Kargashin, P.E. Korosteleva, P.A. Varentsov, A.I. Perkhurova, A.A. Konstantinov, P.I. Lomonosov Moscow State University Research Computing Center Faculty of Geography Moscow Russia A.M. Obukhov Institute of Atmospheric Physic Moscow Russia Hydrometeorological Research Center of Russia Moscow Russia RUDN University Smart Urban Nature Laboratory Moscow Russia

this study considers experience in use of crowdsourced meteorological observations from the world's biggest network of citizen weather stations (CWSs), Netatmo, for urban climate research and applied monitoring services on the example of Moscow megacity. Crowdsourcing paradigm is an emerging alternative to the development of expensive urban meteorological networks. We have experimentally evaluated the uncertainties of the Netatmo temperature observations and regard them as being acceptable when the stations are shadowed from the sun. In order to filter out the misrepresentative observations, a quality-control algorithm has been developed. Within more than 1500 CWSs in the Moscow region, only about 25% meet this quality control, which is still one order of magnitude higher than the number of official Roshydromet weather stations in the study area. Such amount of data opens new opportunities for spatially-resolving urban climate studies and for applied services. As an example of the latter, we present a prototype of a web-mapping application for a near-real-time temperature monitoring system in Moscow. the application's backend includes automatic services for downloading of observations from Netatmo and official Roshydromet networks, as well as for database maintaining. the processed data are visualized interactively in a web browser. the application is available on the Internet at http://***/mosclim/. It will be further developed to include a real-time thermal comfort assessment based on the contemporary PET and UTCI biometeorological indices, a visualization of the interpolated fields, and other improvements. © Published under licence by IOP Publishing Ltd.

关键词： Crowdsourcing

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Weighted record sample for underwater seismic monitoring application 34

Weighted record sample for underwater seismic monitoring app...

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34th international conference on Computers and their applications, CATA 2019

作者： Albarakati, Hussain Ammar, Reda Elfouly, Raafat Computer Science and Engineering Department University of Connecticut StorrsCT06269 United States Computer Science Department Rhode Island College United States

ISBN: (纸本)9781510885967

Underwater acoustic sensor networks have been developed as a new technology for real-time underwater applications, including seismic monitoring, disaster prevention, and oil well inspection. Unfortunately, this new technology is constrained to data sensing, large-volume transmission, and forwarding. As a result, the transmission of large volumes of data is costly in terms of both time and power. We thus focused our research activities on the development of embedded underwater computing systems. In this advanced technology, information extraction is performed underwater using data mining techniques or compression algorithms. We previously presented a new set of real-time underwater embedded system architectures that can manage multiple network configurations. In this study, we extend our research to develop information extraction for seismic monitoring underwater application to meet real-time constraints. the system performance is measured in terms of the minimum end-to-end delay and power consumption. the simulation results are presented to measure the performance of our architecture based on the information extraction algorithm. Copyright © 2012-2020 ***. All rights reserved.

关键词： embedded systems

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Efficient Deterministic Federated Scheduling for Parallel real-time Tasks

Efficient Deterministic Federated Scheduling for Parallel Re...

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IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Son Dinh Christopher Gill Kunal Agrawal Washington University in St. Louis

ISBN: (数字)9781728144030

ISBN: (纸本)9781728144047

Federated scheduling is a generalization of partitioned scheduling for parallel tasks on multiprocessors, and has been shown to be a competitive scheduling approach. However, federated scheduling may waste resources due to its dedicated allocation of processors to parallel tasks. In this work we introduce a novel algorithm for scheduling parallel tasks that require more than one processor to meet their deadlines (i.e., heavy tasks). the proposed algorithm computes a deterministic schedule for each heavy task based on its internal graph structure. It efficiently exploits the processors allocated to each task and thus reduces the number of processors required by the task. Experimental evaluation shows that our new federated scheduling algorithm significantly outperforms other state-of-the-art federated-based scheduling approaches, including semi-federated scheduling and reservation-based federated scheduling, that were developed to tackle resource waste in federated scheduling, and a stretching algorithm that also uses the tasks' graph structures.

关键词： Task analysis Program processors Scheduling Schedules Scheduling algorithms real-time systems

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Preemption-Aware Allocation, Deadline Assignment for Conditional DAGs on Partitioned EDF

Preemption-Aware Allocation, Deadline Assignment for Conditi...

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IEEE international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Houssam-Eddine ZAHAF Giuseppe Lipari Smail Niar Abou El Hassan Benyamina CRIStAL UMR 9189 HiPeRT Lab. Lille University Unimore University CRIStAL UMR 3380 Lille University LAMIH UPHF University LAPECI Oran 1 University

ISBN: (数字)9781728144030

ISBN: (纸本)9781728144047

Heterogeneous hardware platforms are often used for implementing complex critical real-time applications, like Advanced driver-assistance systems (ADAS) and autonomous driving. Typically, they are composed of CPU hosts and a set of accelerators. To better support real-time workloads, several hardware accelerators have evolved to allow preemption for computationally intensive tasks, such as GPUs. However, their preemption costs can be very high compared to classical CPU preemption, and therefore must be taken into account at design time and in the scheduling analysis. In this paper, we address mainly two tightly correlated problems: (i) task allocation for a set of real-time tasks, modeled by conditional directed acyclic graphs (C-DAG), onto multiprocessor platforms under partitioned preemptive Earliest Deadline First scheduling, assuming a non-negligible cost of preemption, and (ii) intermediate deadlines and offsets assignments to real-time C-DAGs, so to remove unnecessary preemption and reduce the total preemption overhead. the effectiveness of the proposed technique is evaluated using a large set of synthetic tasks sets.

关键词： Task analysis real-time systems Processor scheduling Resource management Computational modeling Computer architecture time factors

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Novel Arithmetics to Accelerate Machine Learning Classifiers in Autonomous Driving applications 26

Novel Arithmetics to Accelerate Machine Learning Classifiers...

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26th IEEE international conference on Electronics, Circuits and systems (ICECS)

作者： Cococcioni, Marco Rossi, Federico Ruffaldi, Emanuele Saponara, Sergio Univ Pisa Dept Informat Engn Pisa Italy MMI Spa Pisa Italy

ISBN: (纸本)9781728109961

Autonomous driving techniques frequently need the clustering and the classification of data coming from several input sensors, like cameras, radar and lidars. these sub-tasks need to be implemented in real-time in embedded on-board computing units. the trend for data classification and clustering in the signal processing community is moving towards machine learning (ML) algorithms. One of them, which plays a central role, is the k-nearest neighbors (k-NN) algorithm. To meet stringent requirements in terms of real-time computing capability and circuit/memory complexity, ML accelerators are needed. Innovation is required in terms of computing arithmetic since classic integer numbers lead to low classification accuracy with respect to the needs of safety critical applications like autonomous driving. Instead, floating numbers require too much circuit and memory. To overcome these issues the paper shows that the use of a new format, called Posit, implemented in a new cppPosit software library, can lead to a k-NN implementation having the same accuracy of floats, but with halved bit-size. this means that a Posit Processing Unit ( PPU) reduces by a factor higher than 2 the data transfer and storage complexity of ML accelerators. We also prove that a LUT-based complete tabulated implementation of a PPU for a 8-bit requires just 64 kB storage size, compliant with memory-constrained devices.

关键词： k-Nearest Neighbors (k-NN) Alternative real Representation Posits Machine Learning (ML) Accelerator

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