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Big Data Analytics Platforms for Electric Vehicle Integration in Transport Oriented Smart Cities: Computing Platforms for Platforms for Electric Vehicle Integration in Smart Cities

机译:面向交通智能城市的电动汽车集成大数据分析平台:智能城市电动汽车集成平台的计算平台

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Electric vehicles (EVs) are key players for transport oriented smart cities (TOSC) powered by smart grids (SG) because they help those cities to become greener by reducing vehicle emissions and carbon footprint. In this article, the authors analyze different use-cases to show how big data analytics (BDA) can play vital role for successful electric vehicle (EV) to smart grid (SG) integration. Followed by this, this article presents an edge computing model and highlights the advantages of employing such distributed edge paradigms towards satisfying the store, compute and networking (SCN) requirements of smart EV applications in TOSCs. This article also highlights the distinguishing features of the edge paradigm, towards supporting BDA activities in EV to SG integration in TOSCs. Finally, the authors provide a detailed overview of opportunities, trends, and challenges of both these computing techniques. In particular, this article discusses the deployment challenges and state-of-the-art solutions in edge privacy and edge forensics.
机译:电动汽车(EV)是由智能电网(SG)驱动的面向交通的智能城市(TOSC)的关键参与者,因为它们通过减少车辆排放和碳足迹帮助这些城市变得更加绿色。在本文中,作者分析了不同的用例,以说明大数据分析(BDA)如何在成功地将电动汽车(EV)集成到智能电网(SG)中发挥至关重要的作用。随后,本文介绍了一种边缘计算模型,并重点介绍了采用这种分布式边缘范例来满足TOSC中智能电动汽车应用程序的存储,计算和联网(SCN)要求的优势。本文还重点介绍了边缘范式的显着特征,以支持EV中的BDA活动与TOSC中的SG集成。最后,作者详细介绍了这两种计算技术的机遇,趋势和挑战。特别是,本文讨论了边缘隐私和边缘取证方面的部署挑战和最新解决方案。

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