SEI(IIS): MotionEye: Querying and Mining Large Datasets of Moving Objects

设计和开发强大的机制来管理和挖掘移动物体的大型数据集是科学和工程信息学的一个新兴方向。随着世界以及国家安全威胁变得更加多变，这一主题变得越来越重要。该项目正在研究与查询、分析和挖掘时空信息的创新方法的设计和开发相关的问题，以找到运动物体轨迹的典型特征，并在运动物体的大型数据集中发现可疑运动。移动对象数据集以存储数据或瞬态数据流的形式存在。该项目正在设计和实现MotionEye系统原型，该原型由四个子系统组成：分别用于在移动对象数据库和数据流中查询和假设验证的MotionQuest（DB）和MotionQuest(Stream)，以及分别用于在移动对象数据库和数据流中进行数据挖掘的MotionMine（DB）和MotionMine（Stream）。该项目正在调查实现这些子系统的高效和有效的方法。该项目还努力确保开发的技术不会牺牲个人隐私。该项目将能够在国土安全、执法、交通控制和其他处理移动物体的领域开发更先进的信息系统。

The design and development of powerful mechanisms for managing and mining large datasets of moving objects is an emerging direction in science and engineering informatics. The subject becomes increasingly important as the world, as well as national security threats, become more mobile. This project is investigating the issues related to the design and development of innovative methods for querying, analyzing, and mining of spatiotemporal information to find typical characteristics of the moving objects' trajectories, and uncover suspicious motion in large datasets of moving objects. The moving objects datasets are in the form of either stored data or transient data streams. The project is designing and implementing the MotionEye system prototype which consists of four subsystems: MotionQuest(DB) and MotionQuest(Stream) for querying and hypothesis validation in moving objects databases and data streams respectively, and MotionMine(DB) and MotionMine(Stream) for data mining in moving objects databases and data streams respectively. The project is investigating efficient and effective approaches to the implementation of these subsystems. The project is also striving to ensure that the developed technology will not sacrifice individual privacy. The project will enable the development of more advanced information systems in homeland security, law enforcement, traffic control, and other domains that deal with moving objects.