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Wireless Reality Analytics And Application Research

Posted on:2016-03-08Degree:MasterType:Thesis
Country:ChinaCandidate:D B FuFull Text:PDF
GTID:2298330467491999Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
Human mobility seems out of order, but there is potential model. Song pointed out that the population mobility is non-random and periodic. People always appear in a particular place, activities of the crowd always follow the simple reproduction mode.This paper focus on the Spatial attribute and time attribute of human mobility. Spatial attribute corresponds to human moving physical space (for example, indoor and outdoor). Time attributes corresponds to the moving of crowd with the change of time (for example, a user corresponding dwell time). The study of human mobility is helpful for some specific social problems such as the exploration of traffic planning, city planning, control of influenza and so on. In order to study the population distribution in local region, and predict user mobile trajectory, we design and implement a complete platform of population information collection and data analysis, and introduce the population statistical model, trajectory acquisition model. This paper focuses on the theoretical and verification on these model implementation, and the relevant applications. This paper mainly has following several aspects:1. Investigate the research point and interest focus of population mobility and related technical points of data acquiring and data processing, realizes the mobile terminal data collection through OpenWrt wireless routing nodes.2. Based on the WiCloud platform, we realize the aggregation statistics of different local area people. Based on the simulation of wireless signal propagation through WIFI for indoor and outdoor model, we realize the distinguish of indoor and outdoor people, then complete the flow distribution statistics and show of heat map.3. Based on the periodicity characteristic of human mobility, we analyze the common prediction applicable scene of human mobility prediction model and make the Mobile Markov Chain as the representative, to achieve the user mobile trajectory acquisition and prediction of the population movement, and the application prospect of the related work is presented.
Keywords/Search Tags:human mobility, wireless reality analytics system, trafficstatistics, trajectory prediction
PDF Full Text Request
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