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Systems for delivering electric vehicle data analytics.

机译:用于提供电动汽车数据分析的系统。

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摘要

In the recent times, advances in scientific research related to electric vehicles led to generation of large amounts of data. This data is majorly logger data collected from various sensors in the vehicle. It is predominantly unstructured and non-relational in nature, also called Big Data. Analysis of such data needs a high performance information technology infrastructure that provides superior computational efficiency and storage capacity. It should be scalable to accommodate the growing data and ensure its security over a network. This research proposes an architecture built over Hadoop to effectively support distributed data management over a network for real-time data collection and storage, parallel processing, and faster random read access for information retrieval for decision-making.;Once imported into a database, the system can support efficient analysis and visualization of data as per user needs. These analytics can help understand correlations between data parameters under various circumstances. This system provides scalability to support data accumulation in the future and still perform analytics with less overhead. Overall, these open problems in EV data analytics are taken into consideration and a low-cost architecture for data management is researched.
机译:近年来,与电动汽车相关的科学研究的进展导致产生大量数据。该数据主要是从车辆中各种传感器收集的记录器数据。它本质上主要是非结构化和非关系性的,也称为大数据。对此类数据的分析需要高性能的信息技术基础架构,该基础架构应提供出色的计算效率和存储容量。它应该具有可伸缩性,以适应不断增长的数据并确保其在网络上的安全性。这项研究提出了一种基于Hadoop构建的体系结构,可有效支持网络上的分布式数据管理,以进行实时数据收集和存储,并行处理以及更快的随机读取访问以进行信息检索以进行决策;系统可以根据用户需求支持数据的高效分析和可视化。这些分析可以帮助理解各种情况下数据参数之间的相关性。该系统提供可伸缩性,以支持将来的数据积累,并且仍以较少的开销执行分析。总体而言,考虑到了电动汽车数据分析中的这些开放性问题,并研究了一种低成本的数据管理架构。

著录项

  • 作者

    Bolly, Vamshi K.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Information Technology.;Transportation.;Computer Science.
  • 学位 M.S.
  • 年度 2014
  • 页码 78 p.
  • 总页数 78
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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