English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

help Locations Based Services systems to meet market demands, a performance and scalable collection framework was provided to gather different kinds of geographical data (from GPS devices, RFID, Data base transactions, etc.) based on the unified moving object trajectories' Meta-model. Basically, the collection framework offers components to collect spatio-temporal data from GPS enabling devices using .Net sockets, and benefits from executing all code in .NET Common Language Runtime to increase the system performance compared to unmanaged codes that decrease performance because of additional requirement security checks. In order to test the scalability of the proposed collection system, a vehicle tracking simulator was developed to generate and simulate tremendous spatio-temporal data of different moving objects. The main goal of this manuscript is to illustrate the importance of the collection framework and analyze the worst-case testing. Following this strategy, monitoring how scalable the proposed data collection framework is possible when dealing with very large and simultaneous moving objects trajectories datasets in real time. Keywordsdata modeling, Trajectory data collection framework, moving object database, space time path, spatial data engineering, trajectory meta-model.

A High Performance Scalable Data Collection System for Moving Objects