Indoor room-level positioning method based on Wi-Fi fingerprint database text classification

A technology of text classification and positioning method, which is applied in text database clustering/classification, unstructured text data retrieval, transmission system, etc. It can solve the problem that Wi-Fi signals are easily affected by environmental factors and reduce data dimensions , high efficiency, and the effect of reducing positioning time

Active Publication Date: 2020-06-09
ZHEJIANG UNIV CITY COLLEGE
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Problems solved by technology

But Wi-Fi signal is easily affected by environmental f

Method used

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  • Indoor room-level positioning method based on Wi-Fi fingerprint database text classification
  • Indoor room-level positioning method based on Wi-Fi fingerprint database text classification
  • Indoor room-level positioning method based on Wi-Fi fingerprint database text classification

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Embodiment

[0084] In order to verify the effect of this method positioning, the present invention uses the 2017 Tianchi competition shop positioning data set, and uses the Wi-Fi data of 4 shops (m_615, m_622, m_623, m_625) to verify the present invention. Firstly, mobile hotspots and communication provider hotspots are eliminated from the data of the 4 shops, and a Wi-Fi signal strength fingerprint library is constructed, and according to figure 2 In the manner shown, the signal strength and the number of APs are combined to form words of the short text. The short text data consists of the name of the store as a label, and a short sentence composed of multiple words as a feature.

[0085] By dividing the short text data, the training set and test set are experimented according to the ratio of (50%, 60%, 70%, 80%, 90%), and input into the text classifier to calculate the classification accuracy. Such as image 3 As shown, in this store dataset, it is compared with KNN, Naive Bayes and ...

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Abstract

The invention relates to an indoor room-level positioning method based on Wi-Fi fingerprint database text classification. The indoor room-level positioning method comprises the following steps: firstly, collecting Wi-Fi signal intensity and a basic service set identifier in an indoor environment of a shopping mall; converting the Wi-Fi fingerprint library into short text data; carrying out the feature selection and word weight calculation; adopting a Crammer-Singer support vector classifier; calculating classification accuracy. The method has the beneficial effects that the signal intensity ofWi-Fi is converted into short text words, the influence of the signal intensity is directly ignored, the characteristic of the signal intensity is not considered any more, and a Wi-Fi fingerprint library is reduced; according to the method, the Wi-Fi fingerprint database is converted into the short text data set, the data dimension is reduced, meanwhile, the text classifier is based on the linearkernel SVM classifier, the training and testing efficiency is extremely high, the positioning time can be greatly shortened, and the positioning precision can be greatly improved.

Description

technical field [0001] The invention relates to an indoor room-level positioning method based on text classification of Wi-Fi fingerprint library, mainly using text classification method to carry out indoor room-level positioning on Wi-Fi fingerprint library. Background technique [0002] With the rapid development of mobile communication and pervasive computing technology, various applications are widely trying various technologies for indoor positioning. [0003] Current technologies such as outdoor positioning based on GPS, indoor positioning technology based on geomagnetism, RFID, ZigBee network, Bluetooth, etc. Wi-Fi based positioning is mainly divided into two categories: methods based on location fingerprints and methods based on signal propagation models. Among them, the fingerprint-based indoor positioning system uses Wi-Fi fingerprints composed of multiple access points (APs) and their signal strength (RSSI). But Wi-Fi signals are easily affected by environmental...

Claims

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Application Information

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IPC IPC(8): G06F16/35G06F40/216G06F40/151H04B17/318H04W64/00
CPCG06F16/355H04B17/318H04W64/006
Inventor 郑增威汪振陈垣毅陈丹
Owner ZHEJIANG UNIV CITY COLLEGE
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