Multi-Layer Perceptron Decomposition Architecture for Mobile IoT Indoor Positioning
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Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
No
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Publicly Funded
No
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Top 10%
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Average
Popularity
Top 10%
Abstract
We develop a Multi-Layer Perceptron (MLP) Decomposition architecture for mobile Internet Things (IoT) indoor positioning. We demonstrate the performance of our architecture on an indoor system that utilizes ultra-wideband (UWB) positioning. Our architecture outperforms the following benchmark processing techniques on the same data: MLP Linear Regression Ridge Regression Support Vector Regression and the Least Squares Method for indoor positioning. The results show that our architecture can significantly advance the positioning accuracy of indoor positioning systems and enable indoor applications such as navigation proximity marketing asset tracking collision avoidance and social distancing. © 2021 Elsevier B.V. All rights reserved.
Description
Keywords
Artificial Intelligence (ai), Indoor Positioning, Internet Of Things (iot), Machine Learning (ml), Multi-layer Perceptron (mlp), Ultrawideband (uwb), Architecture, Indoor Positioning Systems, Least Squares Approximations, Machine Learning, Ultra-wideband (uwb), Artificial Intelligence, Indoor Positioning, Indoor Systems, Internet Of Thing, Mobile Internet, Multi-layer Perceptron, Multilayers Perceptrons, Performance, Ultrawideband, Internet Of Things, Architecture, Indoor positioning systems, Least squares approximations, Machine learning, Ultra-wideband (UWB), Artificial intelligence, Indoor positioning, Indoor systems, Internet of thing, Mobile Internet, Multi-layer perceptron, Multilayers perceptrons, Performance, Ultrawideband, Internet of things, Machine Learning (ML), Multi-Layer Perceptron (MLP), Indoor Positioning, Ultrawideband (UWB), Artificial Intelligence (AI), Internet of Things (IoT), Artificial intelligence, Internet of things, Indoor positioning, machine learning (ML), Performance, indoor positioning, Multi-layer perceptron, Artificial Intelligence (AI), Ultrawideband (UWB), Least squares approximations, Multi-Layer Perceptron (MLP), Mobile Internet, Internet of Things (IoT), Ultra-wideband (UWB), Indoor systems, Architecture, Machine learning, Indoor positioning systems, Internet of thing, Multilayers perceptrons, Ultrawideband
Fields of Science
Citation
WoS Q
Scopus Q
OpenCitations Citation Count
7
Source
7th IEEE World Forum on Internet of Things WF-IoT 2021
Volume
Issue
Start Page
253
End Page
257
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Citations
CrossRef : 1
Scopus : 12
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Mendeley Readers : 10
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