A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things
Internet of Things (IoT) is digitizing the world, and indoor positioning is one of the important applications of them. Indoor positioning refers to the realization of positioning in the indoor environment. The recent research on indoor positioning focuses on Wi-Fi-based methods since GPS cannot achi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8746145/ |
| _version_ | 1818620841124954112 |
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| author | Jin Ren Yunan Wang Changliu Niu Wei Song |
| author_facet | Jin Ren Yunan Wang Changliu Niu Wei Song |
| author_sort | Jin Ren |
| collection | DOAJ |
| description | Internet of Things (IoT) is digitizing the world, and indoor positioning is one of the important applications of them. Indoor positioning refers to the realization of positioning in the indoor environment. The recent research on indoor positioning focuses on Wi-Fi-based methods since GPS cannot achieve the desired effect. A core algorithm in those methods is the K nearest neighbor (KNN) search. In this paper, we proposed an improved indoor positioning algorithm named IpKNN with better accuracy and efficiency. The IpKNN mainly includes two parts. The first part is to use the proposed clustering algorithm to classify the data set, which can improve the computational efficiency. The second part is to improve the positioning accuracy by using the proposed KNN algorithm. The proposed algorithm can achieve high precision and low consumption, and the experiment results also proved it. |
| first_indexed | 2024-12-16T17:59:47Z |
| format | Article |
| id | doaj.art-c3aa68e729da43988027ea14af4dac89 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:59:47Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c3aa68e729da43988027ea14af4dac892022-12-21T22:22:05ZengIEEEIEEE Access2169-35362019-01-017868748688310.1109/ACCESS.2019.29249928746145A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of ThingsJin Ren0https://orcid.org/0000-0002-5832-3756Yunan Wang1Changliu Niu2Wei Song3School of Information Science and Technology, North China University of Technology, Beijing, ChinaSchool of Information Science and Technology, North China University of Technology, Beijing, ChinaSchool of Information Science and Technology, North China University of Technology, Beijing, ChinaSchool of Information Engineering, Minzu University of China, Beijing, ChinaInternet of Things (IoT) is digitizing the world, and indoor positioning is one of the important applications of them. Indoor positioning refers to the realization of positioning in the indoor environment. The recent research on indoor positioning focuses on Wi-Fi-based methods since GPS cannot achieve the desired effect. A core algorithm in those methods is the K nearest neighbor (KNN) search. In this paper, we proposed an improved indoor positioning algorithm named IpKNN with better accuracy and efficiency. The IpKNN mainly includes two parts. The first part is to use the proposed clustering algorithm to classify the data set, which can improve the computational efficiency. The second part is to improve the positioning accuracy by using the proposed KNN algorithm. The proposed algorithm can achieve high precision and low consumption, and the experiment results also proved it.https://ieeexplore.ieee.org/document/8746145/Internet of Things (IoT)indoor positioningclusteringKNN algorithmIpKNN |
| spellingShingle | Jin Ren Yunan Wang Changliu Niu Wei Song A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things IEEE Access Internet of Things (IoT) indoor positioning clustering KNN algorithm IpKNN |
| title | A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things |
| title_full | A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things |
| title_fullStr | A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things |
| title_full_unstemmed | A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things |
| title_short | A Novel High Precision and Low Consumption Indoor Positioning Algorithm for Internet of Things |
| title_sort | novel high precision and low consumption indoor positioning algorithm for internet of things |
| topic | Internet of Things (IoT) indoor positioning clustering KNN algorithm IpKNN |
| url | https://ieeexplore.ieee.org/document/8746145/ |
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