Crowd sensing incentive mechanism design method based on trust value

Abstract

The invention discloses a crowd sensing incentive mechanism design method based on a trust value, which comprises the following steps of: collecting historical data information, and establishing an empirical model according to an interaction relationship between two entities, namely a service requester and a task participant, extracted from the historical data information; establishing a reputation model according to the extracted evaluation value of the service requester on the task participant; enabling the service requester to issue a crowd sensing task to the task platform; determining an empirical value of a task participant participating in the task through an empirical model, and determining a reputation value of the task participant participating in the task through a reputation model; calculating a trust value according to the empirical value and the reputation value; if the trust value is not less than the preset trust value threshold, enabling the task participant to obtain the authority of executing the crowd sensing task. The crowd sensing incentive mechanism is designed from the two perspectives of user reputation and task interaction conditions, the users are incentive to participate in the crowd sensing system, meanwhile, the data quality is improved, and malicious users are detected.

Description

technical field [0001] The present invention relates to the technical field of data perception, in particular to a method for designing an incentive mechanism for group intelligence sensing based on trust values. Background technique [0002] Crowd Sensing (CS), a type of crowdsourcing utilizing built-in sensors and applications in smart devices, has recently emerged as a promising solution for distributed sensing and has been widely used in research in the field of the Internet of Things . Crowdsensing is a new data acquisition mode that combines crowdsourcing ideas and mobile device perception capabilities. Crowd intelligence refers to the formation of an interactive and participatory perception network through people's existing mobile devices, and releases perception tasks to individuals or groups in the network to complete, thereby helping professionals or the public to collect data, analyze information and share knowledge. The concept of group intelligence sensing is...

AI Technical Summary

Problems solved by technology

[0005] Publication No. CN110796529A proposes an experience-based incentive policy, which considers the cumulative experience value of service provider users. By introducing an experience model, users can get more rewards by participating in perception tasks and maintaining a higher experience value. However, this model only From the interaction between the task itself and the user, the reputation of the user itself is not considered, and malicious users cannot be judged, which may cause unstable data quality

Images