A method and system for mobile group intelligence perception incentive mechanism based on multi-attribute user selection

Abstract

The invention relates to a method and a system for selecting a mobile group intelligence perception incentive mechanism based on multi-attribute users. Firstly, a perception platform divides a perception task into a plurality of sub-tasks, and sets task utility value, reputation integral threshold value and initial reputation integral value for each sub-task. The perceptual platform publishes subtasks in a flowing manner; perceives the user upload attribute value; The perceptual platform screens the users one by one and determines the optimal set of users by the second screening. The perceptual platform calculates the remuneration obtained by the perceptual user for completing the subtasks according to the remuneration calculation function; perceives whether the user accepts the subtask processing request or not according to the willingness to participate analysis function; The perceptual platform sets up the reward and punishment mechanism of user reputation points, and updates the perceptual user's reputation points. The invention not only can improve the participation degree of the perceptual user and the submitted perceptual data quality, but also can effectively guarantee thequality of the perceptual user and reduce the cost of the system.

Description

technical field [0001] The invention relates to the field of mobile crowd sensing, in particular to a method and system for selecting a mobile crowd sensing incentive mechanism based on multi-attribute users. Background technique [0002] With the popularization and widespread use of various mobile portable sensing devices such as smartphones, tablets, and wearable devices, a new sensing environment, data collection, and information service are provided for the realization of deep ubiquitous social sensing. mode, that is, mobile crowd sensing. Compared with the traditional sensor network that needs to deploy fixed sensors, the mobile crowd sensing network has the advantages of wide sensing range, low cost, and simple maintenance, and is more suitable for large-scale and highly mobile sensing tasks. In the mobile crowd-sensing network, the participation of sensing users is the key factor to determine whether the mobile crowd-sensing system can obtain high-quality data, but v...

AI Technical Summary

Problems solved by technology

Although it can produce corresponding incentive effects to a certain extent, there are problems such as low user participation enthusiasm, a decrease in the proportion of task completion, and an increase in platform consumption costs.

On the one hand, based on the random user selection method, due to the lack of consideration of the user's own characteristics, the user's participation is not high and the data quality level is reduced, which reduces the task completion rate as a whole and increases the platform consumption cost

On the other hand, the user selection method based on a single attribute is a little weak in considering users, and the value of a single attribute cannot fully reflect the characteristics of the user itself, thus weakening the perception platform's ability to screen users, resulting in poor user screening results and platform costs. growing problem

[0004] To sum up, for the problem of how to build an effective incentive mechanism in mobile crowd sensing, the existing solutions are all considered from one aspect, simply solving a certain problem, seriously ignoring other challenges, and cannot comprehensively solve the problem in mobile crowd sensing. of user engagement, user quality, and data quality issues

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