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A Fast and Precise Indoor Localization Algorithm Based on an Online Sequential Extreme Learning Machine

Han Zou, Xiaoxuan Lu, Hao Jiang, Lihua Xie
2015 Sensors  
In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly.  ...  Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments.  ...  Author Contributions Han Zou proposed the OS-ELM-based localization algorithm and expanded the conference version to a journal version.  ... 
doi:10.3390/s150101804 pmid:25599427 pmcid:PMC4327104 fatcat:34ufrv52hzdcpamfmfrxvxfnie

MFA-OSELM Algorithm for WiFi-Based Indoor Positioning System

AL-Khaleefa, Ahmad, Isa, AL-Saffar, Esa, Malik
2019 Information  
This research extends the earlier study of the feature adaptive online sequential extreme learning machine (FA-OSELM).  ...  Thus, this paper presents the maximum feature adaptive online sequential extreme learning machine (MFA-OSELM) technique, which uses previous knowledge to handle the cyclic dynamic factors that are brought  ...  Other researchers chose the online sequential extreme learning machine (OSELM) for WiFi positioning [21] .  ... 
doi:10.3390/info10040146 fatcat:6t73uyz7sfenxovbnsdwvmzqni

A Hybrid Model Based on Constraint OSELM, Adaptive Weighted SRC and KNN for Large-Scale Indoor Localization

Hengyi Gan, Mohd Haris Bin Md Khir, Gunawan Witjaksono Bin Djaswadi, Nordin Ramli
2019 IEEE Access  
INDEX TERMS Constraint online sequential extreme learning machine, k nearest neighbor, weighted sparse representation classification, WiFi-based IPS.  ...  neighbor (KNN) is proposed for the WiFi-based indoor positioning system.  ...  ACKNOWLEDGMENT The author would like to thank great appreciation towards MIMOS for the hardware assistance.  ... 
doi:10.1109/access.2018.2890111 fatcat:dfvnbdwi5bcgpc5iipgkdd2p5y

Sensors for Indoor Mapping and Navigation

Kourosh Khoshelham, Sisi Zlatanova
2016 Sensors  
A fast and precise indoor localization algorithm based on an online sequential extreme learning machine. Sensors 2015, 15, 1804-1824. [CrossRef] [PubMed] 28.  ...  A mixed approach to similarity metric selection in affinity propagation-based WiFi fingerprinting indoor positioning. Sensors 2015, 15, 27692-27720. [CrossRef] [PubMed] 23.  ... 
doi:10.3390/s16050655 pmid:27171079 pmcid:PMC4883346 fatcat:uxkb45tktfeoxfkcrf6b6omh3y

Online Learning-based WIFI Radio Map Updating Considering High-dynamic Environmental Factors

Xiaoguang Niu, Zejun Zhang, Ankang Wang, Jingbin Liu, Shubo Liu
2019 IEEE Access  
In this work, we propose OWUH, an Online Learning-based WIFI Radio Map Updating service considering influences of high-dynamic factors.  ...  An improved online learning method is proposed to recognize periodic pattern and update current radio map.  ...  b: OS-ELM Online sequential extreme learning machine (OS-ELM) [31] , as is shown in Fig. 3 , mainly consists of two phases, namely an initialization phase and an incremental learning phase.  ... 
doi:10.1109/access.2019.2933583 fatcat:tzunx6mw4fgslnpjhxlu5jasmi

A Survey on Fusion-based Indoor Positioning

Xiansheng Guo, Nirwan Ansari, Fangzi Hu, Yuan Shao, Raphael Nkrow, Lin Li
2019 IEEE Communications Surveys and Tutorials  
Index Terms-Indoor positioning based services (IPS), fusion-based positioning, complex electromagnetic environments (CEEs), ensemble learning.  ...  This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced  ...  [55] proposed an MAP-based approach to combine measurements from inertial sensors with TOA measurements from an UWB system for indoor positioning.  ... 
doi:10.1109/comst.2019.2951036 fatcat:7hwlckqvenexvnumbdba22et4m

A Survey of Recent Indoor Localization Scenarios and Methodologies

Tian Yang, Adnane Cabani, Houcine Chafouk
2021 Sensors  
The key localization techniques like RSSI-based fingerprinting technique are presented using supervised machine learning methods, namely SVM (support vector machine), KNN (K nearest neighbors) and NN (  ...  The trilateration is known as a classic theoretical model of geometric-based indoor localization, with uniform RSSI data that can be transferred directly into distance ranges.  ...  ELM (i.e., Extreme Learning Machine) and ensemble ELM methods are proposed by J. Yan et al. [50] to estimate floor-level and object position based on the fingerprint dataset.  ... 
doi:10.3390/s21238086 pmid:34884090 fatcat:juacgglap5f5jaezn3w2lrur3u

Wifi Fingerprint Calibration Using Semi-Supervised Self Organizing Map
반지도식 자기조직화지도를 이용한 wifi fingerprint 보정 방법

Quang Tung Thai, Ki-Sook Chung, Changsup Keum
2017 The Journal of Korean Institute of Communications and Information Sciences  
ABSTRACT Wireless RSSI (Received Signal Strength Indication) fingerprinting is one of the most popular methods for indoor positioning as it provides reasonable accuracy while being able to exploit existing  ...  organizing map learning algorithm.  ...  This feature is extremely beneficial to the practical implementation of indoor positioning system as it is wellknown that radio map needs to be updated frequently due to the fluctuating nature of indoor  ... 
doi:10.7840/kics.2017.42.2.536 fatcat:bte2vkdmenfbzil4o5ri6hkk4y

Using Smart Virtual-Sensor Nodes to Improve the Robustness of Indoor Localization Systems

Guilherme Pedrollo, Andréa Aparecida Konzen, Wagner Ourique de Morais, Edison Pignaton de Freitas
2021 Sensors  
Based on the coordinates of the last measured positions by the unavailable node, a neural network was trained with 4 min of not very linear data to reproduce the behavior of a sensor that become unavailable  ...  Such an approach provided reasonably successful results, especially for areas close to the room's entrances and exits, which are critical for the security monitoring of patients in healthcare facilities  ...  All authors have read and agreed to the published version of the manuscript. Data Availability Statement: Data available on request.  ... 
doi:10.3390/s21113912 fatcat:rng77qwgrnha3gx7zziienun3q

A semi-supervised learning approach for robust indoor-outdoor detection with smartphones

Valentin Radu, Panagiota Katsikouli, Rik Sarkar, Mahesh K. Marina
2014 Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems - SenSys '14  
Implementation of the indoor-outdoor detection service based on our method is lightweight in energy use -it can sleep when not in use and does not need to track the device state continuously.  ...  It can learn and adapt online, in real time, at modest computational costs. Thus the method is suitable for on-device learning.  ...  We thank Charles Sutton for insightful discussions on semi-supervised learning; we thank Lama Nachman and anonymous reviewers for many helpful suggestions on improving the paper.  ... 
doi:10.1145/2668332.2668347 dblp:conf/sensys/RaduKSM14 fatcat:dfv3yx54onhclcpd7ebggmuevy

Laser Range Scanners for Enabling Zero-Overhead WiFi-based Indoor Localization System

Hamada Rizk, Hirozumi Yamaguchi, Moustafa Youssef, Teruo Higashino
2022 ACM Transactions on Spatial Algorithms and Systems  
Towards achieving this goal, WiFi fingerprinting-based indoor localization systems have been proposed.  ...  This paper presents LiPhi++ , an accurate system for enabling fingerprinting-based indoor localization systems without the associated data collection overhead.  ...  The irst author would also like to thank Nvidia for the hardware gift.  ... 
doi:10.1145/3539659 fatcat:yx4rypww65c3bpstb4nok42ryu

Recurrent Neural Networks For Accurate RSSI Indoor Localization [article]

Minh Tu Hoang, Brosnan Yuen, Xiaodai Dong, Tao Lu, Robert Westendorp,, Kishore Reddy
2019 arXiv   pre-print
This paper proposes recurrent neuron networks (RNNs) for a fingerprinting indoor localization using WiFi.  ...  Furthermore, a weighted average filter is proposed for both input RSSI data and sequential output locations to enhance the accuracy among the temporal fluctuations of RSSI.  ...  Due to the wide fluctuation of WiFi signals [3] in an indoor environment, the exact propagation model is difficult to obtain, which makes the fingerprinting approach more favorable.  ... 
arXiv:1903.11703v2 fatcat:ogcut5a6rvd5hbnnnl6unzrk5a

Indoor localization using visible light via two-layer fusion network

Xiansheng Guo, Fangzi Hu, Raphael Nkrow, Lin Li
2019 IEEE Access  
The experiments conducted on an intensity-modulated direct detection system demonstrate that our proposed TLFN is superior to existing fusion-based approaches regardless of the instability and uncertainty  ...  Then, in the online phase, we propose an optimal weights searching algorithm to intelligently determine the optimal weights for fusion localization.  ...  Machine learning methods adopt a similarity metric to differentiate online signal measurement and fingerprint data, like KNN [26] , support vector machine, random forest (RF) [27] , extreme learning  ... 
doi:10.1109/access.2019.2895131 fatcat:jpqpic5wy5gitn2wc5tgt2lwdy

Fingerprinting-Based Indoor Localization with Commercial MMWave WiFi: A Deep Learning Approach

Toshiaki Koike-Akino, Pu Wang, Milutin Pajovic, Haijian Sun, Philip V. Orlik
2020 IEEE Access  
These intermediate channel measurements are further utilized by a deep learning approach for multiple purposes: 1) location-only classification; 2) simultaneous locationand-orientation classification;  ...  Existing fingerprint-based indoor localization uses either fine-grained channel state information (CSI) from the physical layer or coarse-grained received signal strength indicator (RSSI) measurements.  ...  Leveraging modern machine learning frameworks such as discriminant-adaptive neural network [26] , robust extreme learning machines [27] , and multi-layer neural networks [28] , RSSI fingerprinting-based  ... 
doi:10.1109/access.2020.2991129 fatcat:zhxo4m2pfvbbhiaesmxi2aha3i

The election algorithm for semantically meaningful location-awareness

Uzair Ahmad, Brian J. d'Aauriol, Young-Koo Lee, Sungyoung Lee
2007 Proceedings of the 6th international conference on Mobile and ubiquitous multimedia - MUM '07  
It employs an realtime learning approach which requires zero prior knowledge.  ...  This paper presents a simple location estimation method to build radio beacon based location systems in the indoor environments.  ...  CONCLUSIONS AND FUTURE DIREC-TIONS An online, incremental and interactive learning algorithm is presented to develop radio beacon based location estimation system for indoor environments.  ... 
doi:10.1145/1329469.1329476 dblp:conf/mum/AhmaddLL07 fatcat:3jok55ryorgkflbxrs37nocbba
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