Intelligent Planning Method for IoT Sensing Data

Abstract

The present invention provides an intelligent planning method for IoT sensing data. The method includes: virtualizing Internet of Vehicles resources to form heterogeneous services; forming similar services into service groups, and mining, selecting and merging the services in the service group , to complete the scheduling of Internet of Vehicles resources. The present invention proposes an intelligent planning method for IoT sensing data, aiming at the mass and heterogeneous variability of the sensing data of the Internet of Vehicles system, adopting a unified data interface to comprehensively perceive and process heterogeneous information to realize seamless information interaction and standardized sharing between different application system data.

Description

technical field [0001] The present invention relates to the Internet of Things, in particular to an intelligent planning method for IoT sensing data. Background technique [0002] With the rapid development of computers and networks, the status of intelligent transportation in the national economy is becoming more and more important, and the intelligent transportation service model has become an important factor in improving the efficiency of transportation operations, reducing transportation costs, and improving the competitiveness of the entire society. At present, cloud computing has developed to the application landing stage, and has made great achievements in enterprises, search engines, etc., but it has developed slowly in the intelligent transportation industry. Its development poses challenges to modern transportation, and it is no longer limited to data-intensive. Instead, it provides more extensions. Information services based on the Internet of Things and cloud c...

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Problems solved by technology

[0003] At present, the existing solutions for intelligent transportation service models are mainly to develop intelligent transportation information system construction frameworks and data centers from the perspective of information systems; however, service integration does not involve the consideration of innovation in intelligent transportation service models under cluster-side computing environments. That is, there is no system solution for service description, service packaging, service mining and service merging of the Internet of Vehicles

Moreover, the data sensed by the Internet of Vehicles system is massive, multivariate, heterogeneous, and time-space variable. At present, a unified perception data description structure has not been established for the comprehensive perception and processing of heterogeneous information, and it is impossible to standardize event information, associate pairing processing, etc. , it is difficult to realize the seamless interaction of information and the sharing and interoperability between data of different application systems

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