III: Small: AegisDB: Integrated Real-Time Geo-Stream Processing and Monitoring System: A Data-Type-Based Approach

该项目有助于激动人心的地质流处理领域。具体而言，将建立一个名为AegisDB的集成实时地理流处理和监测系统，并利用研究环境和结果来刺激K-12，本科和研究生水平的学习。AegisDB系统包括一个地理流代数，它使用基于数据类型的方法，而不是传统的基于元组的方法来表示和查询地理流。代数的STREAM数据类型统一了静态数据、传统流、来自固定位置的地理流和移动的地理流。建议的聚合代数广义运算符GROUP BY的广义聚合（GAs）和桥梁的传感器和时空连续现象的点观测之间的根本差距。 提出了几种新的以空间为中心的操作优化技术，其中包括基于速度的过滤，利用大多数移动对象的物理限制和基于空间覆盖的查询组合，结合地理流查询的基础上，其预期的空间covery.The拟议的AegisDB系统将改变的方式来定义和监视更复杂的时空事件报警的目的。其结果是大大改善了专业人士和公众对与我们生活有关的重要时空事件的实时访问。该系统将对包括交通、环境科学、危险监测和应急响应在内的重要领域至关重要。 该项目有很强的教育和外联组成部分。 将设计使用实时环境数据集的K-12教师和学生的环境模型。一个关于如何收集、存储和分发环境数据的非正式会议将通过UNT榆树叉教育中心的家庭娱乐科学星期六活动进行介绍。将开发一个关于地理流处理的课程单元。该研究项目将招募女性和少数族裔。寻找研究机会的本科生将得到指导。有关该项目的更多信息，请参见项目网页：URL：http://www.cse.unt.edu/~huangyan/AegisDB/

This project contributes to the exciting field of geo-stream processing. Specifically, an integrated real-time geo-stream processing and monitoring system called AegisDB will be built and the research environment and results will be leveraged to stimulate learning at the K-12, undergraduate, and graduate levels. The AegisDB system includes a Geo-Stream Algebra which uses a data-type-based approach as opposed to a traditional tuple-based approach for representing and querying geo-streams. The STREAM data types of the algebra unify static data, traditional streams, geo-streams from fixed locations, and geo-streams that move. The proposed Aggregate Algebra generalizes the operator GROUP BY to generalized aggregations (GAs) and bridges the fundamental gap between point observations from sensors and spatio-temporally continuous phenomena. Several novel spatial-centric operator optimization techniques are proposed, which include a velocity-based filtering that utilizes the physical limitations of most moving objects and a spatial-coverage-based query combination that combines geo-stream queries based on their intended spatial coverage.The proposed AegisDB system will transform the ways to define and monitor more sophisticated spatio-temporal events for alerting purposes. The result is the significantly improved realtime access to important spatio-temporal events related to our lives by professionals and the general public. The system will be critical for important domains including transportation, environmental science, hazard monitoring, and emergency responses. This project has strong education and outreach components. Environmental models for K-12 teachers and students using real-time environmental datasets will be designed. An informal session on how to collect, store, and distribute environmental data will be presented through the Family Fun Science Saturday events of the Elm Fork Education Center of UNT. A course module on geo-stream processing will be developed. Women and minorities will be recruited into the research project. Undergraduate students looking for research opportunities will be mentored. For further information concerning this project see the project web page: URL: http://www.cse.unt.edu/~huangyan/AegisDB/