@inproceedings{c97612027ce34c289060ff46a6d52079,
title = "Cnnloc: Deep-learning based indoor localization with wifi fingerprinting",
abstract = "With the ubiquitous deployment of wireless systems and pervasive availability of smart devices, indoor localization is empowering numerous location-based services. With the established radio maps, WiFi fingerprinting has become one of the most practical approaches to localize mobile users. However, most fingerprint-based localization algorithms are computationintensive, with heavy dependence on both offline training phase and online localization phase. In this paper, we propose CNNLoc, a Convolutional Neural Network (CNN) based indoor localization system with WiFi fingerprints for multi-building and multifloor localization. Specifically, we devise a novel classification model by combining a Stacked Auto-Encoder (SAE) with a onedimensional CNN. The SAE is utilized to precisely extract key features from sparse Received Signal Strength (RSS) data while the CNN is trained to effectively achieve high success rates in the positioning phase. We evaluate the proposed system on the UJIIndoorLoc dataset and Tampere dataset with several stateof-the-art methods. The results show CNNLoc outperforms the existing solutions with 100% and 95% success rates on buildinglevel localization and floor-level localization, respectively.",
keywords = "Convolutional neural network, Deep learning, Indoor localization, Wifi fingerprinting",
author = "Xudong Song and Xiaochen Fan and Xiangjian He and Chaocan Xiang and Qianwen Ye and Xiang Huang and Gengfa Fang and Chen, {Liming Luke} and Jing Qin and Zumin Wang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 ; Conference date: 19-08-2019 Through 23-08-2019",
year = "2019",
month = aug,
doi = "10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00139",
language = "English",
series = "Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "589--595",
booktitle = "Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019",
address = "United States",
}
