A novel system architecture for real-time, robust and accurate step detection for PDR based indoor localization

Indoor localization is currently of good interest concerning both business viability and end user experience. In this paper, we propose an accurate and robust step detection algorithm for smartphone based pedestrian dead reckoning (PDR) systems. The developed algorithm makes use of the acceleration...

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Vydáno v:2018 IEEE 4th World Forum on Internet of Things (WF-IoT) s. 754 - 759
Hlavní autoři: Kiran, M. P. R. S., Rajalakshmi, P., Giluka, Mukesh Kumar, Tamma, Bheemarjuna Reddy
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.02.2018
Témata:
Acceleration
Accelerometers
Gravity
Indoor localization
Legged locomotion
PDR
Real-time systems
Robustness
SLAM
Step detection
Wireless fidelity
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Abstract Indoor localization is currently of good interest concerning both business viability and end user experience. In this paper, we propose an accurate and robust step detection algorithm for smartphone based pedestrian dead reckoning (PDR) systems. The developed algorithm makes use of the acceleration measured from the smartphone and uses a statistical threshold based classification to detect the steps accurately. The statistical thresholds used are derived from extensive field trials with subjects of different age groups and found to provide good accuracy when used in real-time. For analyzing the performance of the proposed algorithm, we have implemented the algorithm on Android platform and performed extensive field trials. The analysis proves that the proposed algorithm identifies the user steps in real-time with an accuracy of more than 99% with minimum memory requirements.
AbstractList Indoor localization is currently of good interest concerning both business viability and end user experience. In this paper, we propose an accurate and robust step detection algorithm for smartphone based pedestrian dead reckoning (PDR) systems. The developed algorithm makes use of the acceleration measured from the smartphone and uses a statistical threshold based classification to detect the steps accurately. The statistical thresholds used are derived from extensive field trials with subjects of different age groups and found to provide good accuracy when used in real-time. For analyzing the performance of the proposed algorithm, we have implemented the algorithm on Android platform and performed extensive field trials. The analysis proves that the proposed algorithm identifies the user steps in real-time with an accuracy of more than 99% with minimum memory requirements.
Author Rajalakshmi, P.
Kiran, M. P. R. S.
Giluka, Mukesh Kumar
Tamma, Bheemarjuna Reddy
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  givenname: M. P. R. S.
  surname: Kiran
  fullname: Kiran, M. P. R. S.
  email: ee12m1021@iith.ac.in
  organization: WiNet Laboratory, Dept. of Electrical Engineering, Indian Institute of Technlogy Hyderabad, Hyderabad, India
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  surname: Rajalakshmi
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  givenname: Mukesh Kumar
  surname: Giluka
  fullname: Giluka, Mukesh Kumar
  email: cs11p1002@iith.ac.in
  organization: Dept. of Computer Science & Engineering, Indian Institute of Technlogy Hyderabad, Hyderabad, India
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  givenname: Bheemarjuna Reddy
  surname: Tamma
  fullname: Tamma, Bheemarjuna Reddy
  email: tbr@iith.ac.in
  organization: Dept. of Computer Science & Engineering, Indian Institute of Technlogy Hyderabad, Hyderabad, India
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Snippet Indoor localization is currently of good interest concerning both business viability and end user experience. In this paper, we propose an accurate and robust...
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StartPage 754
SubjectTerms Acceleration
Accelerometers
Gravity
Indoor localization
Legged locomotion
PDR
Real-time systems
Robustness
SLAM
Step detection
Wireless fidelity
Title A novel system architecture for real-time, robust and accurate step detection for PDR based indoor localization
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