A method, device and system for indoor position prediction based on motion feature association

Abstract

The embodiment of the invention provides a method, device and system for indoor location prediction based on motion feature association. The method comprises the steps of establishing a circular region model with a to-be-predicted user as the center; comparing a motion state of the to-be-predicted user and a motion state of associated users, and obtaining first associated users and a first similarity between the to-be-predicted user and each first associated user; utilizing recorded values on whether the to-be-predicted user and each associated user are in the same circular region within a firs preset time period prior to a first time point in historical data of user motion states, and obtaining a second similarity of the to-be-predicted user and each first associated user; and utilizing a relationship of a circular region of each first associated user within a second preset time period after the same time point corresponding to the first time point through the first similarity, the second similarity and historical data of motion states of the first associated users in historical data of user motion states to obtain predicted position coordinates of the to-be-predicted user.

Description

technical field [0001] The present invention relates to the field of location services, in particular to an indoor location prediction method, device and system based on motion feature association. Background technique [0002] With the development of sensor technology and positioning technology, location service plays an increasingly important role in people's life. Related research points out that human mobility is highly cyclical and predictable. Mining the user's historical location data, obtaining the regularity of the user's location movement, predicting the user's future mobile location, can provide a variety of location services based on the predicted location, such as providing accurate information push according to the user's running track, especially Indoor areas with large traffic such as shopping malls, airports, and stations. For example, in shopping malls, predict the merchants that users will visit to help merchants push product information and preferential...

AI Technical Summary

Problems solved by technology

Moreover, different from outdoor location prediction, indoor location prediction pays more attention to the user's specific motion state changes and the continuity of user location changes while considering which areas t

Images