Mobile crowd sensing coverage optimization method based on multi-modal trajectory

A mobile crowd sensing and coverage optimization technology, applied in character and pattern recognition, biological neural network models, instruments, etc., can solve problems such as ignoring the use of multi-modal information, and achieve the effect of improving quality

Pending Publication Date: 2022-05-03
HARBIN UNIV OF SCI & TECH
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  • Claims
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AI Technical Summary

Problems solved by technology

However, the existing methods often ignore the utilization of multimodal information. Therefore, from the perspective of multimodal data fusion, this paper expects to improve the coverage rate through multimodal trajectories.

Method used

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  • Mobile crowd sensing coverage optimization method based on multi-modal trajectory
  • Mobile crowd sensing coverage optimization method based on multi-modal trajectory
  • Mobile crowd sensing coverage optimization method based on multi-modal trajectory

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Experimental program
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Embodiment Construction

[0019] Perceive the user's trajectory data from a series of GPS positioning points P i Each GPS potential point includes time and latitude and longitude information, namely P i =(time, latitude, longitude). Connect all GPS points to form the user's trajectory image, such as image 3 shown.

[0020] Divide the perception area into several sub-areas of equal size, set the pixel value of the sub-area covered by the track to 1, and set the pixel value of the uncovered sub-area to 0, then the formation is as follows: Figure 4 The binary map of the trajectory is shown. It can visually represent the area where the user passes by. The trajectory binary map cannot express the location preference of the sensing user, that is, in which areas the sensing user is more likely to accept the sensing task and complete the sensing activity. According to the speed data collected by the speed sensor of the smart device held by the sensing user, the present invention comprehensively consid...

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Abstract

In an existing coverage optimization method based on a perceived user track in mobile crowd sensing, only the moving position of a perceived user is considered, and other information of the user, such as moving speed and environmental noise, is neglected. In order to solve the problem, the invention provides a coverage optimization method based on multi-modal trajectory data fusion. The method comprises the following steps: firstly, analyzing track data characteristics of a user in mobile crowd sensing, judging the influence of moving speed and environmental noise on the acquisition intention of the sensing user, and establishing a speed grey-scale map and a sound grey-scale map; then, fusing the speed grey-scale map and the sound grey-scale map by using a double-branch convolutional neural network to form a track grey-scale map; and finally, sensing user selection is carried out based on the grey-scale map coverage similarity, so that the coverage rate is maximized.

Description

technical field [0001] The invention belongs to the field of mobile group intelligence sensing, and in particular relates to a coverage optimization method based on multimodal trajectories. Background technique [0002] Mobile crowd sensing (Mobile Crowd Sensing, MCS) is a technology that uses the sensors of mobile smart devices to collect data, and uses and researches the collected data. This form of sensing can achieve more flexible and efficient data collection, analysis and application than traditional wireless sensor networks (WSN), especially in large-scale sensing tasks, with low cost and high sensing efficiency. . MCS is a new form of data acquisition that combines crowdsourcing ideas and mobile device perception capabilities, and is a manifestation of the Internet of Things (IoT). MCS forms 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,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/80G06K9/62G06N3/04
CPCG06N3/045G06F18/25
Inventor 刘佳王健赵国生
Owner HARBIN UNIV OF SCI & TECH
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