Thematic event update method library and parallel update method of urban multi-source spatio-temporal information

Abstract

The invention discloses a subject event updating method base and an urban multi-source time-space information parallel updating method. Suggested time-space information updating is related to multiple factors such as information sources, data models and dimension, updating methods, updating technological process, quality control and subject events, and a time-space database is updated on the basis of multi-source data integration and abnormal change discovery. On the basis of time-space database updating, a sudden event updating mechanism, an updating method based on subject event linkage and a GPU (Graphic Processing Unit) parallel acceleration updating algorithm are established, so that the dynamic information updating of urban time-space substances and time-space events is realized specific to the requirements of updating content and frequency of time-space information. The subject event updating method base and the urban multi-source time-space information parallel updating method has the advantages that corresponding data and sensors are updated by the GPU parallel updating algorithm according to the judgment and triggering of corresponding subject events, so that major sudden events concerned by users can be discovered while the time-space information of users is kept newest, and technical support can be provided for emergency safety, traffic dispersion and the like in smart cities.

Description

technical field [0001] The invention belongs to the field of updating spatio-temporal information of smart cities, and relates to a subject event update method library and a parallel update method of urban multi-source spatio-temporal information, in particular to a subject event-based smart city theme event update method library and parallel urban multi-source spatio-temporal information update method. Background technique [0002] The data acquired by various aviation, aerospace, close-range measurement and new sensors, as well as multi-source spatio-temporal information such as the Internet of Things, mobile Internet, and location-based service networks are the basic support for applications such as current urban operation management, construction planning, emergency command, and public services. It is an indispensable and important part of building a "smart city". With the gradual improvement of the construction of the air-ground sensor network, more and more urban spat...

AI Technical Summary

Problems solved by technology

[0005] Existing update methods aim at subject-oriented and efficient spatio-temporal data management update. The storage and management of massive spatio-temporal data has poor expression ability for dynamic targets, single form of management data, insufficient flexibility, and scalability needs to be improved. Structural and unstructured information is difficult to build an efficient index structure and carry out unified management and real-time scheduling, and the current data management and update mainly focus on the update of urban entities, lack of abnormal change discovery and update mechanism for theme events, due to the existence of change identification It is difficult to be theoretically complete and independent due to the many ambiguities in the definition criteria. At the logical level, the spatio-temporal pyramid model and various spatio-temporal relationship models under the conceptual framework of time and geography have relatively flexible geographic and spatio-temporal structured expression capabilities, but Theoretical research work is more than physical realization, and the ability to express basic structural features is still insufficient

[0006] Different from traditional anomaly detection and spatial anomaly detection methods, spatio-temporal anomaly detection needs to take into account the change of spatial entities over time, which is more complicated. Although some scattered results have been obtained, the depth and breadth of the overall research are still insufficient. The developed theory The method is far from mature

In addition to event detection and discovery, GPU-based fast parallel update algorithms have not been applied to spatio-temporal data updates on a large scale.

Images