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Indoor human tracking mechanism using integrated onboard smartphones Wi-Fi device and inertial sensors

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Abstract

In indoor/outdoor environments, special cares need to be given to locate smartphones which are used by most of the people. Locating or tracking is valuable for those people who are in dangerous falling-situations or they are used for shopping and billing services, inside the buildings. This tracking system needs a new positioning mechanism to offer very accurate services to the special needy people. To this end, this paper presents a hybrid mechanism to locate indoors smartphones; specifically Wi-Fi access-points signals are available. The proposed mechanism incorporates onboard Wi-Fi and sensor devices including gyroscopes and accelerometers to provide accurate indoor smart phone positioning. This paper proposes an integrated approach to offer indoor smartphone positioning. The purpose of the integrated approach is to fuse multi-technologies measurements on smartphones. The mechanism uses proximity-level (based on received-signal-strength ‘RSS’ measurement) technique between the smartphone and Wi-Fi access-points which they are exist in the vicinity. Then it combines this proximity measurement with uncertainty calculations from onboard dead-reckoning measurements using Extended-Kalman filter, which can provide seamless, low cost, and improve location accuracy significantly, especially when deep indoor. This means, in deep indoor, the approach can utilize only a single Wi-Fi access-points signals as well as using prior-estimate positions based on artificial conditions. The results from different trial experiments (using Android-based smartphones) show that around 2.5-m positioning accuracy can be obtained.

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Authors and Affiliations

  1. Department of Software Engineering, Faculty of Engineering, Koya University, University Park, Kurdistan Region-F.R., Iraq

    Safar A. Maghdid, Halgurd S. Maghdid & Sherko R. HmaSalah

  2. Department of Computer Science, Faculty of Science, Cihan University-Erbil, Kurdistan, Iraq

    Halgurd S. Maghdid

  3. Department of Software Engineering, Salahaddin University-Erbil, Kurdistan, Iraq

    Kayhan Z. Ghafoor

  4. School of Information Technology, Monash University, 47500, Bandar Sunway, Malaysia

    Ali Safaa Sadiq & Suleman Khan

Authors
  1. Safar A. Maghdid
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  2. Halgurd S. Maghdid
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  3. Sherko R. HmaSalah
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  4. Kayhan Z. Ghafoor
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Correspondence to Ali Safaa Sadiq.

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The authors this paper certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

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Maghdid, S.A., Maghdid, H.S., HmaSalah, S.R. et al. Indoor human tracking mechanism using integrated onboard smartphones Wi-Fi device and inertial sensors. Telecommun Syst 71, 447–458 (2019). https://doi.org/10.1007/s11235-018-0517-2

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  • DOI: https://doi.org/10.1007/s11235-018-0517-2

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