Indoor navigation systems based on data mining techniques in internet of things: a survey

Indoor navigation systems based on data mining techniques in internet of things: a survey Internet of Things (IoT) is turning into an essential part of daily life, and numerous IoT-based scenarios will be seen in future of modern cities ranging from small indoor situations to huge outdoor environments. In this era, navigation continues to be a crucial element in both outdoor and indoor environments, and many solutions have been provided in both cases. On the other side, recent smart objects have produced a substantial amount of various data which demands sophisticated data mining solutions to cope with them. This paper presents a detailed review of previous studies on using data mining techniques in indoor navigation systems for the loT scenarios. We aim to understand what type of navigation problems exist in different IoT scenarios with a focus on indoor environments and later on we investigate how data mining solutions can provide solutions on those challenges. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Networks Springer Journals

Indoor navigation systems based on data mining techniques in internet of things: a survey

Download PDF
18 pages
Read Article

Loading next page...
 
/lp/springer_journal/indoor-navigation-systems-based-on-data-mining-techniques-in-internet-gM3vMRGg1j
Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Communications Engineering, Networks; Computer Communication Networks; Electrical Engineering; IT in Business
ISSN
1022-0038
eISSN
1572-8196
DOI
10.1007/s11276-018-1766-4
Publisher site
See Article on Publisher Site

Abstract

Internet of Things (IoT) is turning into an essential part of daily life, and numerous IoT-based scenarios will be seen in future of modern cities ranging from small indoor situations to huge outdoor environments. In this era, navigation continues to be a crucial element in both outdoor and indoor environments, and many solutions have been provided in both cases. On the other side, recent smart objects have produced a substantial amount of various data which demands sophisticated data mining solutions to cope with them. This paper presents a detailed review of previous studies on using data mining techniques in indoor navigation systems for the loT scenarios. We aim to understand what type of navigation problems exist in different IoT scenarios with a focus on indoor environments and later on we investigate how data mining solutions can provide solutions on those challenges.

Journal

Wireless Networks – Springer Journals

Published: May 29, 2018

References

  • Superior path planning mechanism for mobile beacon-assisted localization in wireless sensor networks
    REzazadeh, J; Moradi, M; Ismail, AS; Dutkiewicz, E
  • Svm-based multimodal classification of activities of daily living in health smart homes: Sensors, algorithms, and first experimental result s
    Fleury, A; Vacher, M; Noury, N
  • The kdd process for extracting useful knowledge from volumes of data
    Fayyad, U; Piatetsky-Shapiro, G; Smyth, P
  • Data mining: Concepts and techniques
    Han, J; Pei, J; Kamber, M
  • The crisp-dm model: The new blueprint for data mining
    Shearer, C
  • A broadband tactile array on the fingertip
    Summers, IR; Chanter, CM
  • Fundamentals of statistical signal processing
    Kay, SM
  • Network navigation: Theory and interpretation
    Shen, Y; Mazuelas, S; Win, MZ
  • Auv navigation and localization: A review
    Paull, L; Saeedi, S; Seto, M; Li, H
  • Travi-navi: Self-deployable indoor navigation system
    Zheng, Y; Shen, G; Li, L; Zhao, C; Li, M; Zhao, F
  • Message-efficient localization in mobile wireless sensor networks
    Rezazadeh, J; Moradi, M; Ismail, AS
  • Mobility increases localizability: A survey on wireless indoor localization using inertial sensors
    Yang, Z; Wu, C; Zhou, Z; Zhang, X; Wang, X; Liu, Y
  • Orientation and mobility in external spaces for blind apprentices using mobile devices
    Sanchez, J; Saenz, M
  • A survey of calibration-free indoor positioning systems
    Hossain, AM; Soh, W-S
  • Location fingerprinting with bluetooth low energy beacons
    Faragher, R; Harle, R
  • Indoor localization and automatic fingerprint update with altered ap signals
    He, S; Lin, W; Chan, S-H
  • A survey on mobile anchor assisted localization techniques in wireless sensor networks
    Halder, S; Ghosal, A
  • Cooperative spatial retreat for resilient drone networks
    Kang, J-H; Kwon, Y-M; Park, K-J
  • Indoor tracking: Theory, methods, and technologies
    Dardari, D; Closas, P; Djurić, PM
  • Survey of wireless indoor positioning techniques and systems
    Liu, H; Darabi, H; Banerjee, P; Liu, J
  • Mobile wireless sensor networks overview
    Rezazadeh, J; Moradi, M; Ismail, AS
  • Impact of static trajectories on localization in wireless sensor networks
    Rezazadeh, J; Moradi, M; Ismail, AS; Dutkiewicz, E
  • Fundamental metrics for wireless sensor networks localization
    Rezazadeh, J; Moradi, M; Ismail, AS
  • A survey on sensor localization
    Wang, J; Ghosh, RK; Das, SK
  • Localization techniques in wireless sensor networks
    Alrajeh, NA; Bashir, M; Shams, B
  • A reverse localization scheme for underwater acoustic sensor networks
    Moradi, M; Rezazadeh, J; Ismail, AS
  • Smartphone inertial sensor-based indoor localization and tracking with ibeacon corrections
    Chen, Z; Zhu, Q; Soh, YC
  • Combining visual natural markers and imu for improved ar based indoor navigation
    Neges, M; Koch, C; König, M; Abramovici, M
  • Navigation system heading and position accuracy improvement through gps and ins data fusion
    Ryu, JH; Gankhuyag, G; Chong, KT
  • Fast heading-rotation-based high-accuracy misalignment angle estimation method for ins and gnss
    Hu, P; Wang, S; Zhang, R; Liu, X; Xu, B
  • The kdd process for extracting useful knowledge from volumes of data
    Fayyad, U; Piatetsky-Shapiro, G; Smyth, P
  • The weka data mining software: An update
    Hall, M; Frank, E; Holmes, G; Pfahringer, B; Reutemann, P; Witten, IH
  • R language definition
    Team, RC
  • Mining fuzzy association rules and fuzzy frequency episodes for intrusion detection
    Luo, J; Bridges, SM
  • Detecting neolithic burial mounds from lidar-derived elevation data using a multi-scale approach and machine learning techniques
    Guyot, A; Hubert-Moy, L; Lorho, T
  • Classification of architectural heritage images using deep learning techniques
    Llamas, J; Lerones, PM; Medina, R; Zalama, E; Gómez-García-Bermejo, J
  • Csi-based fingerprinting for indoor localization: A deep learning approach
    Wang, X; Gao, L; Mao, S; Pandey, S
  • A survey on deep learning in medical image analysis
    Litjens, G; Kooi, T; Bejnordi, BE; Setio, AAA; Ciompi, F; Ghafoorian, M; Laak, JA; Ginneken, B; Sánchez, CI
  • A survey of big data management: Taxonomy and state-of-the-art
    Siddiqa, A; Hashem, IAT; Yaqoob, I; Marjani, M; Shamshirband, S; Gani, A; Nasaruddin, F
  • Rss-based indoor localization using multiplicative distance-correction factor
    Gui, L; Yang, M; Fang, P; Yang, S
  • Recent advances in indoor localization: A survey on theoretical approaches and applications
    Yassin, A; Nasser, Y; Awad, M; Al-Dubai, A; Liu, R; Yuen, C; Raulefs, R
  • Green internet of things for smart world
    Zhu, C; Leung, VC; Shu, L; Ngai, EC-H
  • Evolution of research in health geographics through the international journal of health geographics (2002–2015)
    Pérez, S; Laperrière, V; Borderon, M; Padilla, C; Maignant, G; Oliveau, S
  • Design and development of logistics workflow systems for demand management with rfid
    Lee, CK; Ho, W; Ho, GT; Lau, HC
  • Ensemble of software defect predictors: An ahp-based evaluation method
    Peng, Y; Kou, G; Wang, G; Wu, W; Shi, Y
  • Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts
    García-Osorio, C; Haro-García, A; García-Pedrajas, N
  • A combined wavelet and data-mining based intelligent protection scheme for microgrid
    Mishra, DP; Samantaray, SR; Joos, G
  • Multidimensional social network in the social recommender system
    Kazienko, P; Musial, K; Kajdanowicz, T
  • Clustering by fast search and find of density peaks
    Rodriguez, A; Laio, A
  • Wi-fi fingerprint-based indoor positioning: Recent advances and comparisons
    He, S; Chan, S-HG
  • A classification framework for beacon applications
    Vossen, G; Dillon, S; Schomm, F; Stahl, F
  • Intelligent dynamic radio tracking in indoor wireless local area networks
    Kushki, A; Plataniotis, KN; Venetsanopoulos, AN
  • Building a practical wi-fi-based indoor navigation system
    Han, D; Jung, S; Lee, M; Yoon, G
  • Data aggregation using dynamic selection of aggregation points based on rssi for wireless sensor networks
    Awang, A; Agarwal, S
  • Location-aware communications for 5g networks: How location information can improve scalability, latency, and robustness of 5g
    Taranto, R; Muppirisetty, S; Raulefs, R; Slock, D; Svensson, T; Wymeersch, H
  • Data mining for internet of things: A survey
    Tsai, C-W; Lai, C-F; Chiang, M-C; Yang, LT
  • Privacy and security of patient data in the pathology laboratory
    Cucoranu, IC; Parwani, AV; West, AJ; Romero-Lauro, G; Nauman, K; Carter, AB; Balis, UJ; Tuthill, MJ; Pantanowitz, L
  • Deep neural networks for wireless localization in indoor and outdoor environments
    Zhang, W; Liu, K; Zhang, W; Zhang, Y; Gu, J
  • A survey of crowd sensing opportunistic signals for indoor localization
    Pei, L; Zhang, M; Zou, D; Chen, R; Chen, Y
  • Coordinated robot navigation via hierarchical clustering
    Arslan, O; Guralnik, DP; Koditschek, DE
  • A hybrid knn-svm model for iranian license plate recognition
    Tabrizi, SS; Cavus, N
  • Dynamic indoor navigation with bayesian filters
    Wang, W; Ku, W-S
  • Passive indoor localization based on csi and naive bayes classification
    Wu, Z; Xu, Q; Li, J; Fu, C; Xuan, Q; Xiang, Y

You’re reading a free preview. Subscribe to read the entire article.

Try 2 weeks free now

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

or browse the journals available

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off

Sign up
for free
Start 14 day
Free Trial