@inproceedings{c55d43835e0641e9801f5d630a9bbc05,
title = "A novel algorithm based on clustering and access points selection for indoor fingerprint localization",
abstract = "With the growing popularity of location-based service(LBS), wireless local area networks(WLAN) indoor positioning has gained widespread attention. Unlike the traditional algorithm concentrating on positioning accuracy, we discuss how to improve the real-time property in WLAN indoor fingerprinting localization systems. In this paper, we present a novel algorithm which first divides the positioning area into sub-areas utilizing k-means clustering, and then selects appropriate access points(APs) for positioning to make the calculated amount as less as possible. By collecting data and performing in the real WLAN environment, our proposed algorithm shows high positioning accuracy while the computational burden has been decreased almost 93.7\%.",
keywords = "Access points selection, Indoor positioning, K-means clustering, Location fingerprinting, WLAN",
author = "Xing Zhang and Lin Ma and Tan, \{Xue Zhi\} and Guo, \{Shi Zeng\}",
year = "2013",
doi = "10.4028/www.scientific.net/AMR.756-759.3527",
language = "英语",
isbn = "9783037857700",
series = "Advanced Materials Research",
pages = "3527--3531",
booktitle = "Information Technology Applications in Industry, Computer Engineering and Materials Science",
note = "3rd International Conference on Materials Science and Information Technology, MSIT 2013 ; Conference date: 14-09-2013 Through 15-09-2013",
}