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检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

共 3239 条记录，以下是251-260 订阅

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DEVELOPING USER- AND TECHNOLOGY-DRIVEN USE CASES FOR smart CITY APPLICATIONS 16

DEVELOPING USER- AND TECHNOLOGY-DRIVEN USE CASES FOR SMART C...

引用

16th international conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected smart Cities, CSC 2022, 7th international conference on Big data analytics, data Mining and Computational Intelligence, BigDaCI 2022, and 11th international conference on Theory and Practice in Modern computing, TPMC 2022 - Held at the 16th Multi conference on Computer Science and Information Systems, MCCSIS 2022

作者： Otto, Robert Guedey, Myriam Uckelmann, Dieter University of Applied Sciences Stuttgart Schellingstraße 24 Stuttgart70174 Germany

ISBN: (纸本)9789898704429

Within the transformation and digitalization in the area of smart public buildings and infrastructures, finding, selecting and implementing the "right" use cases is an actual challenge for cities, public utilities, and other stakeholders. The question is where to start, what knowledge and capacities are available and what should be prioritized. This paper introduces a first concept for a methodology that supports the co-development of use cases with respect to current activities, existing infrastructures, and know-how on behalf of the public partners. As a preliminary result, three use cases were identified that represent the current priorities of the involved partner smart cities. © MCCSIS *** rights reserved.

关键词： Internet of things

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Toward Effective and Sustainable smart City Model Case study exploration of varying smart city approaches and outcomes 20

Toward Effective and Sustainable Smart City Model Case study...

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21st Annual international conference on Digital Government Research (DGO) - intelligent Government in the intelligent Information Society

作者： Ahn, Michael Chen, Yu-Che Cho, KiHaing Huang, Chengyu (Victor) Kim, Younhee Myeong, Seung-Hwan Univ Massachusetts Dept Publ Policy & Publ Affairs Boston MA 02125 USA Univ Nebraska Digital Governance & Analyt Lab Omaha NE 68182 USA Busan Metropolitan City Busan South Korea Univ Nebraska Aviat Inst UAS Lab Coll Publ Affairs & Community Serv Omaha NE 68182 USA Penn State Harrisburg Sch Publ Affairs Middletown PA USA Inha Univ Dept Publ Adm Incheon South Korea

ISBN: (纸本)9781450387910

This panel aims to explore selected cases of smart city projects to improve our understanding of the critical institutional factors and processes that lead to effective and sustainable smart city outcomes. This panel discusses compelling smart city cases, including Busan Metropolitan City, Songdo, Gimpo, and Namyang-ju. These cases apply different approaches to run smart city practices that are characterized as either a large-scale, top-down, capital-intensive and hardware-focused smart city project or a small-scale, bottom-up, less capital-intensive and data-training focused (as opposed to hardware-focused) smart city project. This panel will highlight the varying outcomes and impacts of different smart city approaches and identify key institutional factors and strategies that contribute to effective and sustainable smart city outcomes.

关键词： smart government smart government models government innovation data analytics drone

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Visual Analysis of the Bibliometric data Associated with the Calibration of Car-Following Models 20

Visual Analysis of the Bibliometric Data Associated with the...

引用

20th Annual international conference on Distributed computing in smart Sensor Systems and the Internet of Things (DCOSS-IoT)

作者： Pop, Madalin-Dorin Micea, Mihai, V Politehn Univ Timisoara Comp & Informat Technol Dept Timisoara Romania

ISBN: (纸本)9798350369458;9798350369441

intelligent transportation systems (ITS) use the latest technologies for real-time traffic control and monitoring to ensure efficient traffic management and reduce the risks of traffic accidents. The microscopic level of traffic modeling is the most appropriate level for controlling and monitoring the interaction between vehicles based on car-following scenarios. However, the data retrieved from sensor networks can be affected by measurement errors, and consequently the implementation of appropriate mechanisms to overcome their propagation to the control system is mandatory. This paper aims to analyse the current research in the calibration of car-following models and provide valuable insights of recent developments in this field. To achieve this goal, VOSviewer has been chosen as a visualisation tool to create bibliographic maps based on the output from the well-known scientific database Clarivate analytics Web of Science (WoS). The maps obtained provide a visual representation of the main institutions involved in this field of research and identify the research interests based on author and indexing keywords. Furthermore, this paper analyses the top five clusters identified based on the analysis of co-occurrence keywords, presenting discussions about the connections existing within these clusters.

关键词： bibliometric analysis calibration car-following model intelligent transportation systems VOSviewer

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Development and Risk of smart City

Development and Risk of Smart City

引用

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Chen, Yanping Long, Minghui Wuhan Donghu University Hubei China

ISBN: (纸本)9783030627423

smart city is the development direction of future urban construction and the main driving force to promote sustainable urban development. In this paper, starting from the concept of intelligent city, profound interpretation of the wisdom of the city development and technical support. At the same time, in view of the wisdom urban construction existing in the information security risk, weak top-level design and problems of traditional urban management discussion, and explore the corresponding Suggestions and countermeasures, in order to promote the construction of wisdom city better and faster. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart city

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Energy-Efficient Energy analytics Using a General Purpose Graphics Processing Unit 8

Energy-Efficient Energy Analytics Using a General Purpose Gr...

引用

8th IEEE international conference on Big data (Big data)

作者： De, Sagnik Golab, Wojciech Univ Waterloo Elect & Comp Engn Waterloo ON Canada

ISBN: (纸本)9781728162515

smart meters allow energy providers to monitor their customers' power consumption. This fine-grained data stream generates many data points, which hides broader trends in power consumption and makes it difficult for energy providers to make decisions regarding a specific customer or a subset of customers. Since the raw power data has little direct use, various algorithms have been proposed to lower the dimensionality of data, discover trends, study relationships between different features of collected data, and summarize data. These analytical techniques make the data more palatable to the end user. Analyzing smart meter data is computationally intensive as there is a large number of households connected to one energy provider, and each household generates years of data at hourly intervals. To speed up the analysis, clusters of commodity computers have been used. Ironically, such clusters consume substantial energy - studies have shown that about 10% of the world-wide supply of electrical power is consumed by the computing infrastructure. In this paper, we describe the use of a graphics processing unit (GPU) to analyze smart meter data, and compare its performance with a conventional multi-core CPU. We discuss the technical challenges in programming a GPU effectively to process smart meter data, and demonstrate experimentally that this choice of implementation enables substantial improvements in terms of both running time and energy-efficiency as compared to the multi-core CPU.

关键词： smart grid smart electricity meters data analytics parallel processing GPU energy-efficiency scalability

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The Impact of COVID-19 Experience on smart City and Future Mobility 9th

The Impact of COVID-19 Experience on Smart City and Future ...

引用

9th international conference on smart Cities and Green ICT Systems, smartGREENS 2020, and 6th international conference on Vehicle Technology and intelligent Transport Systems, VEHITS 2020

作者： Gusikhin, Oleg Global Data Insight and Analytics Ford Motor Company 22001 Michigan Avenue DearbornMI United States

ISBN: (纸本)9783030891695

This paper discusses the challenges and opportunities of the existing technologies and practices in the context of smart City and Future Mobility to cope with pandemics. The overview shows a need to accelerate the deployment of smart City and smart Mobility technologies and revisit strategic supply chain planning models. It shows that advancements in IoT, communication, AI and analytics play a crucial role in enabling rapid innovation in order to address immediate needs raised by COVID-19. The overview and discussion focus on five areas: smart City Technologies, Robust Supply Chain of critical items, smart Mobility, Connected and intelligent Vehicles, and Ambient Intelligence. © 2021, Springer Nature Switzerland AG.

关键词： Supply chains

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A Review on Machine Learning Trends, Application and Challenges in Internet of Things 7

A Review on Machine Learning Trends, Application and Challen...

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7th international conference on computing, Communications and Informatics (ICACCI)

作者： Reddy, R. Ravinder Mamatha, Ch Reddy, R. Govardhan CBIT Hyderabad India JBIET Hyderabad Telangana India

ISBN: (纸本)9781538653142

The rapid growth of the internet and its connecting devices makes the things connected to the entire world. In these days, the world is running on the internet of things (IoT), with the increased communication capability and most effective way of communication and transmission lines many of things are connected to the internet. The advent and revolution in smart sensor technology attracts many of the users and most of the devices are connected to the internet. Internet connected sensors and devices generate exponential data. Knowingly or unknowingly IoT is generating lots of data. This data is significant in decision making system, but the problem is how to segregate this data for the future analysis purposes. The Internet of Things (IoT) offers engineering teams an innovative way to collect data and observe the status of their products, services and equipment in the field. Machine learning techniques are used to learn from these data to make the device or thing intelligent. For example, using the machine learning identifying the abnormalities from our wearable and taking necessary actions like calling doctor and ambulance automatically when it necessary.

关键词： machine learning data analytics Internet of things smart city

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Computer Performance Determination System Based on Big data Distributed File

Computer Performance Determination System Based on Big Data ...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Lu, Kong Jiangxi Modern Polytech Coll Nanchang 330095 Jiangxi Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The high concurrency, high scalability, high performance, high availability, and large capacity of the distributed file system make it an ideal choice for storing large amounts of data. To determine the performance of the distributed computer in big data analysis, it is necessary to compare the performance test of different distributed file systems. This paper compares the different distributed file systems, analyzes the computer performance characteristics of distributed files, and summarizes the rules of different characteristics.

关键词： Big data Distributed file system Performance decision

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Graphical Perception for Immersive analytics 27

Graphical Perception for Immersive Analytics

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27th IEEE conference on Virtual Reality and 3D User Interfaces (IEEE VR)

作者： Whitlock, Matt smart, Stephen Szafir, Danielle Albers Univ Colorado Boulder CO 80309 USA

ISBN: (纸本)9781728156088

Immersive analytics (IA) uses immersive virtual and augmented reality displays for data visualization and visual analytics. Designers rely on studies of how accurately people interpret data in different visualizations to make effective visualization choices. However, these studies focus on data analysis in traditional desktop environments. We lack empirical grounding for how to best visualize data in immersive environments. This study explores how people interpret data visualizations across different display types by measuring how quickly and accurately people conduct three analysis tasks over five visual channels: color, size, height, orientation, and depth. We identify key quantitative differences in performance and user behavior, indicating that stereo viewing resolves some of the challenges of visualizations in 3D space. We also find that while AR displays encourage increased navigation, they decrease performance with color-based visualizations. Our results provide guidelines on how to tailor visualizations to different displays in order to better leverage the affordances of IA modalities.

关键词： Human-centered computing Visualization Empirical studies in visualization Human-centered computing Human computer interaction (HCI) Interaction paradigms Mixed / augmented reality Human-centered computing Human computer interaction (HCI) Interaction paradigms Virtual reality

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A Review on Edge to Cloud: Paradigm Shift from Large data Centers to Small Centers of data Everywhere 5

A Review on Edge to Cloud: Paradigm Shift from Large Data Ce...

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5th international conference on Inventive Computation Technologies (ICICT)

作者： Uddin, Mohammed Yousuf Ahmad, Sultan Prince Sattam Bin Abdulaziz Univ Coll Comp Engn & Sci Al Kharj Saudi Arabia

ISBN: (纸本)9781728146850

In present, Information Communication Technologies is shifting from large data centers to small and micro data centers, bringing data analytics and storage near to the devices at the edge of networks. This helps to deal with latency and data transition overhead that helps to make real-time operations more efficient. Advent of IoT and smart mobile technologies, new devices are joining networks and generating enormous data. Instead of cloud servers performing data analysis and storage, edge devices and edge servers are sharing the load of cloud servers which will enable hyper-efficient and smart ecosystem for enterprises. This research work addresses the key benefits of edge-to-cloud computing, its challenges and limitations. It also explored the edge architecture and application which are applicable in the current scenario and future possibilities of edge to cloud computing.

关键词： Cloud computing Edge computing Edge Architecture IoT Edge-Center

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