A mobile crowd-sensing method and system

Abstract

The invention discloses a mobile group intelligence perception method and system. The method comprises the following steps: screening all grid units which are always within sufficient perception coverage within a preset time span from a target perception area to obtain a corresponding target grid unit set; screening a mobile node subset that can satisfy the perception coverage demand of all grid units in the target grid unit set within each coverage period from a mobile node set; merging all mobile node subsets corresponding to all coverage periods to obtain a target mobile node set; and performing group intelligence perception by using the target mobile node set. By adoption of the mobile group intelligence perception method and system disclosed by the invention, the number of mobile nodes performing perception data sampling within each coverage period is reduced on the condition of ensuring sufficient coverage of the grid units, thereby effectively reducing the sampling redundancy and energy loss in a group intelligence perception process.

Description

technical field [0001] The present invention relates to the technical field of crowd sensing, in particular to a mobile crowd sensing method and system. Background technique [0002] Mobile crowd sensing is a new type of sensing mode, which uses GPS, microphones, cameras and other sensor devices embedded in smart mobile devices to efficiently collect sensing data, and then transmits sensing data through cellular mobile networks (3G / 4G) or WiFi Sent to the remote sensing platform, the sensing platform will perform data cleaning, database storage, and data analysis and mining on the collected sensing data, so as to provide good decision support for upper-level service applications, and then provide users with universal services. The participation of mobile users is one of the most important characteristics of mobile crowd sensing, and the mobile characteristics of mobile users also provide unprecedented opportunities for sensing coverage and data transmission. [0003] Covera...

AI Technical Summary

Problems solved by technology

Finally, if and only if a mobile node is sampling in the sub-area, it is considered that the sub-area is truly covered. Therefore, coverage is associated with the sampling frequency of the mobile node. Frequent sampling will make the area more likely to However, it will also lead to excessive energy consumption, which will reduce the enthusiasm of mobile users to participate in providing information, and then affect the application quality of mobile crowd sensing

[0004] At present, mobile crowd sensing applications generally use certain incentive mechanisms to attract mobile users to participate in mobile crowd sensing tasks. In this process, some mobile users who contribute less to sensing coverage will also participate in sensing tasks, and then lead to sampling redundancy and unnecessary power consumption

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