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C‐CNNLoc: Constrained CNN for robust indoor localization with building boundary

التفاصيل البيبلوغرافية
العنوان: C‐CNNLoc: Constrained CNN for robust indoor localization with building boundary
المؤلفون: Y. Oh, H.‐M. Noh, W. Shin
المصدر: Electronics Letters, Vol 57, Iss 10, Pp 422-425 (2021)
بيانات النشر: Wiley, 2021.
سنة النشر: 2021
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Computer communications, Mobile radio systems, Automated buildings, Local area networks, Neural nets, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Abstract To enable accurate and reliable indoor localization in a multi‐building environment, a novel constrained convolutional neural network (CNN)‐based indoor localization system (C‐CNNLoc) is proposed using WiFi fingerprinting approach. The proposed network has a sequential structure that firstly classifies a building, followed by estimating the user's location coordinate within the pre‐detected building. Furthermore, the location accuracy is improved by introducing a new loss function that incorporates a penalty term associated with the building boundary. Experimental results illustrate that the proposed method outperforms the existing solutions on the average distance error. The gain comes from that the approach tailored to a multi‐building indoor localization with the sequential structure is prone to successfully correct outliers, that is, predicted location coordinates that lie outside the buildings.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1350-911X
0013-5194
Relation: https://doaj.org/toc/0013-5194; https://doaj.org/toc/1350-911X
DOI: 10.1049/ell2.12142
URL الوصول: https://doaj.org/article/b04ef314b8a9422ea6f9b0fad76f3af6
رقم الأكسشن: edsdoj.b04ef314b8a9422ea6f9b0fad76f3af6
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1350911X
00135194
DOI:10.1049/ell2.12142