Urban sensors are an important part of urban infrastructures and are usually heterogeneous.
Urban sensors with different uses vary greatly in hardware structure, communication …

The volume of spatio-temporal data is growing at a rapid pace due to advances in location-
aware devices, eg, smartphones, and the popularity of location-based services, eg …

With the widespread use of mobile and sensing devices, and the popularity of online map-
based services, such as navigation services, the volume of spatio-temporal data is growing …

Continuous top-k trajectory similarity Search (C k Search) is now commonly required in real-
time large-scale trajectory analysis, enabling the distributed stream processing engines to …

Many kinds of spatio-temporal data in our daily lives, such as the trajectory data of moving
objects, stream natively. Streaming systems exhibit significant advantages in processing …

Massive data streams from sensors in Internet of Things (IoT) and smart devices with Global
Positioning System (GPS) are now flooding to database systems for further processing and …

Previous work on the spatio-temporal index often adopts a simple linear model to predict the
future positions of moving objects, which may generate numerous errors for complex road …

时空流的高效管理要求顾及数据的时空相关性, 支持时空流的高速插入, 实时索引和低延迟时空
范围查询, 而现有的基于HBase 等的存储方案, 因索引更新开销过大, 无法满足高效管理要求 …

Emerging applications over spatio-temporal trajectories require representing the data from
diverse aspects. We study multi-attribute trajectories each of which consists of a sequence of …

In this paper, we proposed an efficient R-tree construction method by bulk loading over
spatial-temporal data stream. The core idea is to partition spatial-temporal data stream into …