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Hybrid Deep Learning Model Based Indoor Positioning Using Wi-Fi RSSI Heat Maps for Autonomous Applications

Alwin Poulose, Dong Seog Han
2020 Electronics  
The experiment results show that a combination of convolutional neural network and long short-term memory network (CNN-LSTM) used in the proposed HDLM outperforms other deep learning models and gives a  ...  The existing Wi-Fi RSSI based positioning systems use raw RSSI signals obtained from APs and estimate the user positions.  ...  The CNN based Wi-Fi system provides accurate building and floor prediction for indoor localization.  ... 
doi:10.3390/electronics10010002 fatcat:k3ju3znrc5eovfp7eokgimo7oa

Vision based Indoor Localization Method via Convolution Neural Network

Zeyad Farisi, Tian Lianfang, Li Xiangyang, Zhu Bin
2019 International Journal of Advanced Computer Science and Applications  
Existing indoor localization methods have bottleneck constraints such as multipath effect for Wi-Fi based methods, high cost for ultra-wide-band based methods and poor anti-interference for Bluetooth-based  ...  In order to avoid these problems, a vision-based indoor localization method is proposed.  ...  So in the Wi-Fi based indoor localization system, additional device is not necessary.  ... 
doi:10.14569/ijacsa.2019.0100709 fatcat:tkbabxpazfddhmhxfs7t7y5qs4

A Framework for CSI-Based Indoor Localization with 1D Convolutional Neural Networks [article]

Liping Wang, Sudeep Pasricha
2022 arXiv   pre-print
In this paper, we propose an end-to-end solution including data collection, pattern clustering, denoising, calibration and a lightweight one-dimensional convolutional neural network (1D CNN) model with  ...  Recently, considerable progress has been made in Channel State Information (CSI) based indoor localization with signal fingerprints.  ...  Stable and accurate indoor localization capabilities are particularly crucial in highly sensitive indoor positioning use cases, such as human activity recognition in hospitals, and robot tracking and position  ... 
arXiv:2205.08068v1 fatcat:7fyib6rtpzdsdept7avkhwgipu

Deep-Learning-Based Wi-Fi Indoor Positioning System Using Continuous CSI of Trajectories

Zhongfeng Zhang, Minjae Lee, Seungwon Choi
2021 Sensors  
point and mobile device of Wi-Fi.  ...  To fully exploit the trajectory CSI's spatial and temporal information, the proposed IPS employs a deep learning network of a one-dimensional convolutional neural network-long short-term memory (1DCNN-LSTM  ...  Compared to GPS signals, Wi-Fi signals are more stable in indoor environments because of their wide deployment and easy access; thus, the utilization of Wi-Fi signals to achieve accurate indoor localization  ... 
doi:10.3390/s21175776 pmid:34502668 pmcid:PMC8434353 fatcat:nfbrr2wviff2bns5lsiqmws3wm

The Adaptive Fingerprint Localization in Dynamic Environment

Keliu Long, Chongwei Zheng, Kun Zhang, Chuan Tian, Chong Shen
2022 IEEE Sensors Journal  
Indoor localization service is an indispensable part of modern intelligent life, among which Wi-Fi based fingerprint localization system is popular in indoor positioning researches due to its advantages  ...  However, Wi-Fi based localization system is susceptible to dynamic environment, and fingerprint collection and updating are time-consuming and labor-intensive.  ...  Among these technologies, Convolutional Neural Network (CNN) and CNN-based hybrid network based are widely used in various fingerprint matching tasks [20] , because CNN can extract robust spatial features  ... 
doi:10.1109/jsen.2022.3175742 fatcat:icaotnztozedtbrvfb27lqefvy

DSCP: Depthwise Separable Convolution-Based Passive Indoor Localization Using CSI Fingerprint

Chong Han, Wenjing Xun, Lijuan Sun, Zhaoxiao Lin, Jian Guo, Miguel Garcia-Pineda
2021 Wireless Communications and Mobile Computing  
Wi-Fi-based indoor localization has received extensive attention in wireless sensing.  ...  However, most Wi-Fi-based indoor localization systems have complex models and high localization delays, which limit the universality of these localization methods.  ...  As traditional classification algorithms, kNN and Bayesian classification are widely used in fingerprint-based localization. There are many fingerprint-based localizations in Wi-Fi wireless sensing.  ... 
doi:10.1155/2021/8821129 fatcat:zotinntjbvdx3hwar7qdhqeooy

A Survey of Machine Learning for Indoor Positioning

Ahasanun Nessa, Bhagawat Adhikari, Fatima Hussain, Xavier Fernando
2020 IEEE Access  
In [115] , the authors propose CiFi based on Deep Convolutional Neural Network (DCNN) with commodity 5GHz Wi-Fi.  ...  Feature extraction and classification are carried out by a DL algorithm known as Convolutional Neural Network (CNN) [115] .  ... 
doi:10.1109/access.2020.3039271 fatcat:htzgf2mwp5gmjbx3cczg5rl7ru

Research on Wi-Fi indoor positioning in a smart exhibition hall based on received signal strength indication

Qing Yang, Shijue Zheng, Ming Liu, Yawen Zhang
2019 EURASIP Journal on Wireless Communications and Networking  
To improve the management of science and technology museums, this paper conducts an in-depth study on Wi-Fi (wireless fidelity) indoor positioning based on mobile terminals and applies this technology  ...  Three different improvement strategies are proposed for the nearest neighbor classification algorithm: a balanced joint metric based on distance weighting and a compromise between the two.  ...  Acknowledgements The authors thank the anonymous reviewers and editors for their efforts in valuable comments and suggestions.  ... 
doi:10.1186/s13638-019-1601-3 fatcat:pvoqpqfhxjc35of2cwhi7kg2gm

A Review of Wi-Fi-Based Traffic Detection Technology in the Field of Intelligent Transportation Systems

Yongjie Lin, Qihang Li, Duanya Lyu, Xiaofei Wang
2022 Buildings  
As the core infrastructure of traffic data collection in the field of Intelligent Transportation Systems (ITS), Wi-Fi-based traffic detectors have great potential for use in traffic target positioning,  ...  To further demonstrate the effectiveness of Wi-Fi-based ITS applications in practice, this study compares with the various Wi-Fi-involved models and algorithms around the world, as well as provides some  ...  The results showed that for trains with a relatively stable collection of Bluetooth devices in proximity and not-so-stable GPS signal, the precision of classification based on Bluetooth and Wi-Fi proximity  ... 
doi:10.3390/buildings12040428 fatcat:zd6nydkatjhbnensxdluyjj3sq

HPIPS: A High-Precision Indoor Pedestrian Positioning System Fusing WiFi-RTT, MEMS, and Map Information

Lu Huang, Baoguo Yu, Hongsheng Li, Heng Zhang, Shuang Li, Ruihui Zhu, Yaning Li
2020 Sensors  
First of all, in view of the non-line-of-sight and multipath problems faced by the radio-signal-based indoor positioning technology, a method of using deep convolutional neural networks to learn the nonlinear  ...  mapping relationship between indoor spatial position and Wi-Fi RTT (round-trip time) ranging information is proposed.  ...  A deep convolutional neural network model is proposed to learn the mapping relationship between indoor spatial location and Wi-Fi RTT ranging information.  ... 
doi:10.3390/s20236795 pmid:33261188 pmcid:PMC7731165 fatcat:hqbqmz7hvrcq7hwqokb3e5c2vm

LC-DNN: Local Connection Based Deep Neural Network for Indoor Localization with CSI

Wen Liu, Hong Chen, Zhongliang Deng, Xinyu Zheng, Xiao Fu, Qianqian Cheng
2020 IEEE Access  
1D-CNN [23] 1.28 1.05 ConFi: Convolutional Neural Networks Based Indoor Wi-Fi Localization Using Channel State Information 2D-CNN [20] 1.41 2.7 CSI-based autoencoder classification for  ...  Among various methods, Wi-Fi fingerprinting is widely used in indoor localization due to the widespread deployment of Wi-Fi infrastructures.  ... 
doi:10.1109/access.2020.3000927 fatcat:dcxkw64psfgl5c4vjza4r4j3cu

Deep Learning for Fingerprint Localization in Indoor and Outdoor Environments

Da Li, Yingke Lei, Xin Li, Haichuan Zhang
2020 ISPRS International Journal of Geo-Information  
In this paper, we proposed a Wi-Fi and magnetic field-based localization system based on deep learning.  ...  Considering the state-of-the-art application of deep learning in image classification, we design a location fingerprint image using Wi-Fi and magnetic field fingerprints for localization.  ...  SVM and DNN were used for indoor and outdoor localization [24] . By using convolution neural network, a hybrid wireless fingerprint localization method was proposed for indoor localization [25] .  ... 
doi:10.3390/ijgi9040267 doaj:6e1d449edb6f4459af9e24b1ec072a56 fatcat:a3fk2b5dm5czfocsxhppmllaq4

C-GCN: A Flexible CSI Phase Feature Extraction Network for Error Suppression in Indoor Positioning

Wen Liu, Qianqian Cheng, Zhongliang Deng, Mingjie Jia
2021 Entropy  
In this paper, a phase feature extraction network based on multi-dimensional correlation is proposed, named Cooperation-Graph Convolution Network (C-GCN).  ...  Graph neural network has performed well in many fields in recent years, but there is still a lot of room to explore in the field of indoor positioning.  ...  Convolutional neural networks on graphs with fast localized spectral filtering. Adv. Neural Inf. Process. Syst.2016, 29, 3844–3852.  ... 
doi:10.3390/e23081004 fatcat:dgwgwai4lrg7rbzpn4bv6vajs4

Fine-grained CSI fingerprinting for indoor localisation using convolutional neural network

Haoyu Zhang, Guoxiang Tong, Naixue Xiong
2020 IET Communications  
To improve the accuracy of Wi-Fi indoor positioning, this study proposes an indoor positioning algorithm based on fine-grained channel state information (CSI) and convolutional neural network (CNN).  ...  As an important positioning source of indoor positioning technology, Wi-Fi signals have attracted the attention of researchers for a long time.  ...  Acknowledgments This work was supported by the National Key Research and Development Program Projects under grant no. 2018YFB1700902. References  ... 
doi:10.1049/iet-com.2020.0156 fatcat:irzyvjhekjcj7ebpnvwnf7b2wy

Wireless Indoor Localization Using Convolutional Neural Network and Gaussian Process Regression

Zhang, Wang, Chen, Zhang
2019 Sensors  
This paper presents a localization model employing convolutional neural network (CNN) and Gaussian process regression (GPR) based on Wi-Fi received signal strength indication (RSSI) fingerprinting data  ...  The trained CNN model improves the positioning performance by taking a series of RSSI vectors into account and extracting local features.  ...  Conclusions This paper has proposed a wireless indoor localization model using convolutional neural network and Gaussian process regression.  ... 
doi:10.3390/s19112508 fatcat:yt75tuexbbfa3keue2jscjkciy
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