Moving object map analytics: A framework enabling contextual spatial-temporal analytics of Internet of Things applications

Wei Sun, Jun Zhu, Ning Duan, Peng Gao, G. Hu, Weishan Dong, Zhi Hu Wang, Xin Zhang, Peng Ji, Chunyang Ma, Jingchang Huang
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引用次数: 12

Abstract

Moving objects, for example vehicles, vessels, people, are being instrumented with Internet of Things devices such as GPS, environmental sensors, mobile cameras that produce big streaming data with spatial-temporal features enabling application innovations in many industries for autonomous driving, usage based insurance, fleet management, etc. We introduce an analytics framework to streamline the insights discovery from such big data on top of geographic map by pulling together a list of commonly required high performance functions with service-oriented architecture. Supported by a service composition approach, comprehensive applications intelligently managing moving objects could be built effectively. Example applications in connected vehicle domains are presented to illustrate the effectiveness of such a framework.
移动对象地图分析:一个框架,支持物联网应用的上下文时空分析
移动物体,如车辆、船只、人员,正在被物联网设备(如GPS、环境传感器、移动摄像头)检测,这些设备可以产生具有时空特征的大数据流,从而在许多行业实现应用创新,如自动驾驶、基于使用的保险、车队管理等。我们引入了一个分析框架,通过将通常需要的高性能功能与面向服务的体系结构结合在一起,来简化从地理地图上的大数据中发现见解的过程。在服务组合方法的支持下,可以有效地构建智能管理移动对象的综合应用程序。通过在车联网领域的应用实例,说明了该框架的有效性。
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