Indoor intelligent fingerprint-based localization: Principles, approaches and challenges

X Zhu, W Qu, T Qiu, L Zhao… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
With the rapid development of Internet of Things (IoT) technology, location-based services
have been widely applied in the construction of smart cities. Satellite-based location …

Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation

H Navidan, PF Moshiri, M Nabati, R Shahbazian… - Computer Networks, 2021 - Elsevier
Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute
an extensively-researched machine learning sub-field for the creation of synthetic data …

Improved symmetric and nonnegative matrix factorization models for undirected, sparse and large-scaled networks: A triple factorization-based approach

Y Song, M Li, X Luo, G Yang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Undirected, sparse and large-scaled networks existing ubiquitously in practical engineering
are vitally important since they usually contain rich information in various patterns. Matrix …

Home automation using IoT and a chatbot using natural language processing

CJ Baby, FA Khan, JN Swathi - 2017 Innovations in Power and …, 2017 - ieeexplore.ieee.org
Home automation-controlling the fans, lights and other electrical appliances in a house
using Internet of things is widely preferred in recent days. In this paper, we propose a web …

Multisource selective transfer framework in multiobjective optimization problems

J Zhang, W Zhou, X Chen, W Yao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
For complex system design [eg, satellite layout optimization design (SLOD)] in practical
engineering, when launching a new optimization instance with another parameter …

Using synthetic data to enhance the accuracy of fingerprint-based localization: A deep learning approach

M Nabati, H Navidan, R Shahbazian… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Human-centered data collection is typically costly and implicates issues of privacy. Various
solutions have been proposed in the literature to reduce this cost, such as crowd-sourced …

Passive infrared sensor dataset and deep learning models for device-free indoor localization and tracking

K Ngamakeur, S Yongchareon, J Yu, S Islam - Pervasive and Mobile …, 2023 - Elsevier
Location estimation or localization is one of the key components in IoT applications such as
remote health monitoring and smart homes. Amongst device-free localization technologies …

New trends in indoor positioning based on WiFi and machine learning: A systematic review

V Bellavista-Parent, J Torres-Sospedra… - 2021 International …, 2021 - ieeexplore.ieee.org
Currently there is no standard indoor positioning system, similar to outdoor GPS. However,
WiFi signals have been used in a large number of proposals to achieve the above …

Chefs' random tables: Non-trigonometric random features

V Likhosherstov, KM Choromanski… - Advances in …, 2022 - proceedings.neurips.cc
We introduce chefs' random tables (CRTs), a new class of non-trigonometric random
features (RFs) to approximate Gaussian and softmax kernels. CRTs are an alternative to …

Comprehensive analysis of applied machine learning in indoor positioning based on wi-fi: An extended systematic review

V Bellavista-Parent, J Torres-Sospedra… - Sensors, 2022 - mdpi.com
Nowadays, there are a multitude of solutions for indoor positioning, as opposed to standards
for outdoor positioning such as GPS. Among the different existing studies on indoor …