Research On Participant-oriented Selection Methods In Mobile Group Intelligence Perception Tasks

The updating speed of the mobile terminal equipment is obvious to all.With the advent of more and more advanced mobile devices,the combination of mobile sensing and crowdsourcing ideas has produced a new type of Internet of Things perception mode,namely the mobile crowd sensing described in this paper.At present,the mobile crowd sensing network has been widely used in social life.The staff is dispatched to a specific location to perform a certain perceived task.However,due to the different purposes of the task publisher,some task publishers hope to obtain Higher quality data,and some task publishers prefer to be able to quickly recruit and select from the task participants.The main content of this paper is to propose a better participant recruitment algorithm for different task publishers.The main results include:A method for recruiting participants based on data quality(herein referred to as CAP-T)is proposed.The method is directed to multiple sensing tasks with short time periods and wanting to obtain higher perceived quality.This paper mainly considers the credibility of workers,the ability of workers and the distance between workers and task location.It controls the cost of task publishers to a certain extent while maximizing the quality of expected results.A heuristic algorithm solves this problem.Simulation experiments show that the CAP-T algorithm can effectively reduce the average error rate and budget utilization compared with the current best methods.A method of participant selection based on space-time utility(herein referred to as TS-PSV)is proposed,which is aimed at a large-scale,single task that needs to quickly recruit participants,wants to obtain higher perceived quality and has a long task period.In this paper,the total task is divided into multiple subtasks with the same status.In each subtask,the budget is not considered separately,taking into account the time trajectory and location information of the actor,maximizing the space-time coverage utility of the participants,and adopting the heuristic algorithm solves this problem.The simulation experiments show that the TS-PSV algorithm can significantly increase the number of participants and improve the space-time utility of the perceived task,while ensuring that the participant selection process time is similar.