Introduction to Spatio-temporal data management and analytics for Smart City research

A Data Analytics Framework for Smart Grids: Spatio-temporal Wind Power Analysis and Synchrophasor Data Mining

Under the framework of intelligent management of power grids by leveragingadvanced information, communication and control technologies, a primary objectiveof this study is to develop novel data mining and data processing schemes for severalcritical applications that can enhance the reliability of power systems. Specifically,this study is broadly organized into the following ...

The STARK Framework for Spatio-Temporal Data Analytics on Spark

Big Data sets can contain all types of information: from server log files to tracking information of mobile users with their location at a point in time. Apache Spark has been widely accepted for Big Data analytics because of its very fast processing model. However, Spark has no native support for spatial or spatio-temporal data. Spatial filters or joins using, e.g., a contains predicate are no...

Spatio-Temporal Big Data Analytics for Environmental Health

The framework for our proposed big data analytics platform is shown in Figure 1. Two complimentary systems support the wide variety of spatial analytics algorithms and techniques we are providing. On the left half of Figure 1, the more-traditional unix filesystem supports high-throughput computation (e.g., MPI [Snir et al., 1995], OpenMP [Dagum and Menon, 1998], GPGPU/CUDA Luebke et al. [2006])...

Uncertainty-aware Visual Analytics for Spatio-temporal Data Exploration

Relational Algebra for Spatio-Temporal Data Management

A generic data type for time is defined as the set In = {1, 2, ..., n} , n > 0 [2]. The elements of In are called quanta of time or (time) instants. Based on this data type, another generic data type is defined, PERIOD(In), with elements of the form [p, q] ≡ { i | i ∈ In, p ≤ i ≤ q} that are called periods (of time). If the elements of In are replaced by n consecutive dates, then the respective...