The Quest for Scalable and Intelligent Trajectory Data Analytics Systems: Status Report and Future Directions

Rim Moussa, A. Haddad, T. Bejaoui
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引用次数: 2

Abstract

A large volume of sensor networks and trajectories of mobile objects are collected. Such data offer us high value knowledge to understand moving objects and locations, fostering a broad range of applications in smart cities, enabling intelligent transportation systems and intelligent urban computing. The next generation of roads needs to be intelligent to accommodate a future transition to fully autonomous vehicles. Consequently, we need to engineer scalable and smart Trajectory Data Analytics Systems in order to analyze both historical data and real-time data flows, derive insights and convert insights into decisions and actions.The purpose of this paper is first to identify key functional and non-functional requirements that a Trajectory Data Analytical system must provide and second to survey open-source technologies designed for the analysis of general geo-referenced data.
对可扩展和智能轨迹数据分析系统的探索:现状报告和未来方向
收集了大量的传感器网络和移动物体的轨迹。这些数据为我们了解移动物体和位置提供了高价值的知识,促进了智能城市的广泛应用,实现了智能交通系统和智能城市计算。下一代道路需要智能化,以适应未来向全自动驾驶汽车的过渡。因此,我们需要设计可扩展的智能轨迹数据分析系统,以分析历史数据和实时数据流,获得见解并将见解转化为决策和行动。本文的目的首先是确定轨迹数据分析系统必须提供的关键功能和非功能需求,其次是调查用于分析一般地理参考数据的开源技术。
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