Outlier detection in indoor localization and Internet of Things (IoT) using machine learning

Article


Bhatti, Mansoor Ahmed, Riaz, Rabia, Rizvi, Sanam Shahla, Shokat, Sana, Riaz, Farina and Kwon, Se Jin. 2020. "Outlier detection in indoor localization and Internet of Things (IoT) using machine learning." Journal of Communications and Networks. 22 (3), pp. 236-243. https://doi.org/10.1109/JCN.2020.000018
Article Title

Outlier detection in indoor localization and Internet of Things (IoT) using machine learning

ERA Journal ID5080
Article CategoryArticle
AuthorsBhatti, Mansoor Ahmed (Author), Riaz, Rabia (Author), Rizvi, Sanam Shahla (Author), Shokat, Sana (Author), Riaz, Farina (Author) and Kwon, Se Jin (Author)
EditorsBhatti, Mansoor Ahmed
Journal TitleJournal of Communications and Networks
Journal Citation22 (3), pp. 236-243
Number of Pages8
Year2020
Place of PublicationKorea
ISSN1229-2370
1976-5541
Digital Object Identifier (DOI)https://doi.org/10.1109/JCN.2020.000018
Web Address (URL)https://ieeexplore.ieee.org/abstract/document/9143576
Abstract

In Internet of things (IoT) millions of devices are intel- ligently connected for providing smart services. Especially in in- door localization environment, that is one of the most concerning topic of smart cities, internet of things and wireless sensor net- works. Many technologies are being used for localization purpose in indoor environment and Wi-Fi using received signal strengths (RSSs) is one of them. Wi-Fi RSSs are sensitive to reflection, re- fraction, interference and channel noise that cause irregularity in signal strengths. The irregular and anomalous RSS values, used in a Wi-Fi indoor localization environment, cannot define the location of any unknown node correctly. Therefore, this research has de- veloped an outlier detection technique named as iF_Ensemble for Wi-Fi indoor localization environment by analyzing RSSs us- ing the combination of supervised, unsupervised and ensemble ma- chine learning methods. In this research isolation forest (iForest) is used as an unsupervised learning method. Supervised learning method includes support vector machine (SVM), K-nearest neigh- bor (KNN) and random forest (RF) classifiers with stacking that is an ensemble learning method. For the evaluation purpose accu- racy, precision, recall, F-score and ROC-AUC curve are used. The evaluation of used machine learning method provides high accu- racy of 97.8 percent with proposed outlier detection methods and almost 2 percent improvement in the accuracy of localization pro- cess in indoor environment after eliminating outliers.

KeywordsInternet of things, localization, outliers, outliers de- tection
ANZSRC Field of Research 2020460609. Networking and communications
Byline AffiliationsUniversity of Azad Jammu and Kashmir, Pakistan
Raptor Interactive, South Africa
Kangwon National University, Korea
Institution of OriginUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/q6v9v/outlier-detection-in-indoor-localization-and-internet-of-things-iot-using-machine-learning

  • 62
    total views
  • 42
    total downloads
  • 2
    views this month
  • 3
    downloads this month

Export as

Related outputs

Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach
Riaz, Farina, Abdulla, Shahab, Suzuki, Hajime, Ganguly, Srinjoy, Deo, Ravinesh C. and Hopkins, Susan. 2023. "Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach." Sensors. 23 (5), pp. 1-11. https://doi.org/10.3390/s23052753
Coloured image classification with quantum machine learning algorithms for intelligent transportation systems
Ria, Farina. 2023. Coloured image classification with quantum machine learning algorithms for intelligent transportation systems. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z014z
An Enhanced Architecture to Resolve Public-Key Cryptographic Issues in the Internet of Things (IoT), Employing Quantum Computing Supremacy
Shamshad, Shuhab, Riaz, Farina, Riaz, Rabia, Rizvi, Sanam Shahla and Abdulla, Shahab. 2022. "An Enhanced Architecture to Resolve Public-Key Cryptographic Issues in the Internet of Things (IoT), Employing Quantum Computing Supremacy." Sensors. 22 (21), pp. 1-24. https://doi.org/10.3390/s22218151
Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
Riaz, Farina, Abdulla, Shahab, Ni, Wei, Radfar, Mohsen, Deo, Ravinesh and Hopkins, Susan. 2022. "Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing." Quantum Australia Conference 2022. Online 23 - 25 Feb 2022 Toowoomba, Australia. https://doi.org/10.13140/RG.2.2.34754.66245
A hybrid architecture for resolving cryptographic issues in Internet of Things (IoT), employing quantum computing supremacy
Shamshad, Shuhab, Riaz, Farina, Riaz, Rabia, Rizvi, Sanam Shahla and Abdulla, Shahab. 2021. "A hybrid architecture for resolving cryptographic issues in Internet of Things (IoT), employing quantum computing supremacy." 12th International Conference on Information and Communication Technology Convergence (ICTC 2021). Jeju Island, Korea, Republic of Korea 20 - 22 Oct 2021 Jeju Island, Korea, Republic of Korea. https://doi.org/10.1109/ICTC52510.2021.9621208
Impact of Web 2.0 on digital divide in AJ&K Pakistan
Shokat, Sana, Riaz, Rabia, Rizvi, Sanam Shahla, Riaz, Farina, Aziz, Samaira, Hussain, Raja Shoaib, Abbasi, Mohaib Zulfiqar and Shabir, Saba. 2018. "Impact of Web 2.0 on digital divide in AJ&K Pakistan." International Journal of Advanced Computer Science and Applications. 9 (2), pp. 221-228. https://doi.org/10.14569/IJACSA.2018.090231
Designing of cell coverage in light fidelity
Riaz, Rabia, Rizvi, Sanam Shehla, Riaz, Farina, Shokat, Sana and Mughall, Naveed Akbar. 2018. "Designing of cell coverage in light fidelity." International Journal of Advanced Computer Science and Applications. 9 (3), pp. 44-53. https://doi.org/10.14569/IJACSA.2018.090308
Analysis of web based structural security patterns by employing ten security principles
Riaz, Rabia, Rizvi, Sanam Shehla, Riaz, Farina, Hameed, Nausheen and Shokat, Sana. 2017. "Analysis of web based structural security patterns by employing ten security principles." International Journal of Computer Science and Network Security. 17 (10), pp. 45-56.
Analysis and evaluation of Braille to Text conversion methods
Shokat, Sana, Riaz, Rabia, Rizvi, Sanam Shahla, Khan, Khalil, Riaz, Farina and Kwon, Se Jin. 2020. "Analysis and evaluation of Braille to Text conversion methods." Mobile Information Systems. 2020, pp. 1-14. https://doi.org/10.1155/2020/3461651
A comparative study of supervised machine learning techniques for diagnosing mode of delivery in medical sciences
Hussain, Syeda Sajida, Riaz, Rabia, Fatima, Tooba, Rizvi, Sanam Shehla, Riaz, Farina and Kwon, Se Jin. 2019. "A comparative study of supervised machine learning techniques for diagnosing mode of delivery in medical sciences." International Journal of Advanced Computer Science and Applications. 10 (12), pp. 120-125. https://doi.org/10.14569/IJACSA.2019.0101216