@inproceedings{6a53a23a6f4b41589071cd62ad1958f0,
title = "A power-efficient scheme for outdoor localization",
abstract = "With the extensive use of smart phones, location-based services are becoming prevalent. Global Positioning System (GPS) is a widely-adopted localization method. However, it drains the battery of smart phones quickly and it is vulnerable to weak GPS signals. GSM-based localization is more robust, but it only leads to low localization precision, which cannot meet the requirements of many location-based services. With the pervasive deployment of WiFi, WiFi-based localiza-tion has become a promising indoor localization method. Nevertheless, simply applying indoor localization methods to outdoor metropolitan environments does not work well. In this paper, we present a hybrid out-door localization scheme, which leverages WiFi signals and the built-in sensors in smart phones to achieve high localization precision and low power consumption. Our experimental results show that the proposed hybrid scheme outperforms the widely-adopted GPS method in terms of localization precision and power consumption.",
keywords = "Fingerprinting, Outdoor localization, Power efficiency",
author = "Kang Yao and Hongwei Du and Qiang Ye and Wen Xu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 12th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2017 ; Conference date: 19-06-2017 Through 21-06-2017",
year = "2017",
doi = "10.1007/978-3-319-60033-8\_46",
language = "英语",
isbn = "9783319600321",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "534--545",
editor = "Yan Zhang and Abdallah Khreishah and Mingyuan Yan and Liran Ma",
booktitle = "Wireless Algorithms, Systems, and Applications - 12th International Conference, WASA 2017, Proceedings",
address = "德国",
}