IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v8y2023i1p14-d1022177.html
   My bibliography  Save this article

UTMInDualSymFi: A Dual-Band Wi-Fi Dataset for Fingerprinting Positioning in Symmetric Indoor Environments

Author

Listed:
  • Asim Abdullah

    (Telecommunication Software and Systems Research Group, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor Bahru, Malaysia)

  • Muhammad Haris

    (Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor Bahru, Malaysia
    Department of Computer Science & Bioinformatics, Khushal Khan Khattak University, Karak 27200, Pakistan)

  • Omar Abdul Aziz

    (Wireless Communication Centre, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor Bahru, Malaysia)

  • Rozeha A. Rashid

    (Telecommunication Software and Systems Research Group, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor Bahru, Malaysia)

  • Ahmad Shahidan Abdullah

    (Telecommunication Software and Systems Research Group, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81310, Johor Bahru, Malaysia)

Abstract

Recent studies on indoor positioning using Wi-Fi fingerprinting are motivated by the ubiquity of Wi-Fi networks and their promising positioning accuracy. Machine learning algorithms are commonly leveraged in indoor positioning works. The performance of machine learning based solutions are dependent on the availability, volume, quality, and diversity of related data. Several public datasets have been published in order to foster advancements in Wi-Fi based fingerprinting indoor positioning solutions. These datasets, however, lack dual-band Wi-Fi data within symmetric indoor environments. To fill this gap, this research work presents the UTMInDualSymFi dataset, as a source of dual-band Wi-Fi data, acquired within multiple residential buildings with symmetric deployment of access points. UTMInDualSymFi comprises the recorded dual-band raw data, training and test datasets, radio maps and supporting metadata. Additionally, a statistical radio map construction algorithm is presented. Benchmark performance was evaluated by implementing a machine-learning-based positioning algorithm on the dataset. In general, higher accuracy was observed, on the 5 GHz data scenarios. This systematically collected dataset enables the development and validation of future comprehensive solutions, inclusive of novel preprocessing, radio map construction, and positioning algorithms.

Suggested Citation

  • Asim Abdullah & Muhammad Haris & Omar Abdul Aziz & Rozeha A. Rashid & Ahmad Shahidan Abdullah, 2023. "UTMInDualSymFi: A Dual-Band Wi-Fi Dataset for Fingerprinting Positioning in Symmetric Indoor Environments," Data, MDPI, vol. 8(1), pages 1-38, January.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:1:p:14-:d:1022177
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/8/1/14/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/8/1/14/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aina Nadhirah Nor Hisham & Yin Hoe Ng & Chee Keong Tan & David Chieng, 2022. "Hybrid Wi-Fi and BLE Fingerprinting Dataset for Multi-Floor Indoor Environments with Different Layouts," Data, MDPI, vol. 7(11), pages 1-20, November.
    2. Germán Martín Mendoza-Silva & Philipp Richter & Joaquín Torres-Sospedra & Elena Simona Lohan & Joaquín Huerta, 2018. "Long-Term WiFi Fingerprinting Dataset for Research on Robust Indoor Positioning," Data, MDPI, vol. 3(1), pages 1-17, January.
    3. Fernando J. Aranda & Felipe Parralejo & Fernando J. Álvarez & Joaquín Torres-Sospedra, 2020. "Multi-Slot BLE Raw Database for Accurate Positioning in Mixed Indoor/Outdoor Environments," Data, MDPI, vol. 5(3), pages 1-20, July.
    4. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    5. Germán Martín Mendoza-Silva & Miguel Matey-Sanz & Joaquín Torres-Sospedra & Joaquín Huerta, 2019. "BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning," Data, MDPI, vol. 4(1), pages 1-17, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emilio Sansano-Sansano & Fernando J. Aranda & Raúl Montoliu & Fernando J. Álvarez, 2020. "BLE-GSpeed: A New BLE-Based Dataset to Estimate User Gait Speed," Data, MDPI, vol. 5(4), pages 1-15, December.
    2. Agnieszka A. Tubis & Katarzyna Grzybowska, 2022. "In Search of Industry 4.0 and Logistics 4.0 in Small-Medium Enterprises—A State of the Art Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    3. Achour Achroufene, 2023. "RSSI-based Hybrid Centroid-K-Nearest Neighbors localization method," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(1), pages 101-114, January.
    4. Viktoriia Shubina & Sylvia Holcer & Michael Gould & Elena Simona Lohan, 2020. "Survey of Decentralized Solutions with Mobile Devices for User Location Tracking, Proximity Detection, and Contact Tracing in the COVID-19 Era," Data, MDPI, vol. 5(4), pages 1-40, September.
    5. Estefania Tobon-Valencia & Samir Lamouri & Robert Pellerin & Alexandre Moeuf, 2022. "Modeling of the Master Production Schedule for the Digital Transition of Manufacturing SMEs in the Context of Industry 4.0," Sustainability, MDPI, vol. 14(19), pages 1-28, October.
    6. Eleonora Di Maria & Valentina De Marchi & Ambra Galeazzo, 2022. "Industry 4.0 technologies and circular economy: The mediating role of supply chain integration," Business Strategy and the Environment, Wiley Blackwell, vol. 31(2), pages 619-632, February.
    7. Germán Martín Mendoza-Silva & Miguel Matey-Sanz & Joaquín Torres-Sospedra & Joaquín Huerta, 2019. "BLE RSS Measurements Dataset for Research on Accurate Indoor Positioning," Data, MDPI, vol. 4(1), pages 1-17, January.
    8. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Bertha Leticia Treviño-Elizondo & Heriberto García-Reyes, 2023. "An Employee Competency Development Maturity Model for Industry 4.0 Adoption," Sustainability, MDPI, vol. 15(14), pages 1-29, July.
    10. Lemstra, Mary Anny Moraes Silva & de Mesquita, Marco Aurélio, 2023. "Industry 4.0: a tertiary literature review," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    11. Hsing-Chun Hung & Yuh-Wen Chen, 2023. "Striving to Achieve United Nations Sustainable Development Goals of Taiwanese SMEs by Adopting Industry 4.0," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    12. Irina Albãstroiu & Calcedonia Enache & Andrei Cepoi & Adrian Istrate & Teodora Liliana Andrei, 2021. "Adopting IoT-Based Solutions for Smart Homes. The Perspective of the Romanian Users," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 325-325.
    13. Guillermo Fuertes & Jorge Zamorano & Miguel Alfaro & Manuel Vargas & Jorge Sabattin & Claudia Duran & Rodrigo Ternero & Ricardo Rivera, 2022. "Opportunities of the Technological Trends Linked to Industry 4.0 for Achieve Sustainable Manufacturing Objectives," Sustainability, MDPI, vol. 14(18), pages 1-36, September.
    14. Csizmadia Tibor & Obermayer Nóra & Bogdány Eszter & Purnhauser Pál & Banász Zsuzsanna, 2023. "Examining Industry 4.0 through the lens of human resource and knowledge management: Implications for SMEs," Management & Marketing, Sciendo, vol. 18(1), pages 1-19, March.
    15. Jang, Hyunmi & Haddoud, Mohamed Yacine & Roh, Saeyeon & Onjewu, Adah-Kole Emmanuel & Choi, Taeeun, 2023. "Implementing smart factory: A fuzzy-set analysis to uncover successful paths," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    16. Sehrish Atif & Shehzad Ahmed & Muhammad Wasim & Bassam Zeb & Zeeshan Pervez & Lorraine Quinn, 2021. "Towards a Conceptual Development of Industry 4.0, Servitisation, and Circular Economy: A Systematic Literature Review," Sustainability, MDPI, vol. 13(11), pages 1-27, June.
    17. Shih-Chia Chang & Hsu-Hwa Chang & Ming-Tsang Lu, 2021. "Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    18. Muhammad Hamza Naseem & Jiaqi Yang, 2021. "Role of Industry 4.0 in Supply Chains Sustainability: A Systematic Literature Review," Sustainability, MDPI, vol. 13(17), pages 1-23, August.
    19. Theerasak Nitlarp & Theeraya Mayakul, 2023. "The Implications of Triple Transformation on ESG in the Energy Sector: Fuzzy-Set Qualitative Comparative Analysis (fsQCA) and Structural Equation Modeling (SEM) Findings," Energies, MDPI, vol. 16(5), pages 1-26, February.
    20. Danilo Ferreira de Souza & Emeli Lalesca Aparecida da Guarda & Welitom Ttatom Pereira da Silva & Ildo Luis Sauer & Hédio Tatizawa, 2022. "Perspectives on the Advancement of Industry 4.0 Technologies Applied to Water Pumping Systems: Trends in Building Pumps," Energies, MDPI, vol. 15(9), pages 1-17, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:8:y:2023:i:1:p:14-:d:1022177. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.