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Tytuł artykułu

Inertial Sensors Integrated with Clothing to Localize People Inside Buildings

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This article presents a wearable system that localizes people in the indoor environment, using data from inertial sensors. The sensors measure the parameters of human motion, tracking the movements of the torso and foot. For this purpose, they were integrated with shirt and the shoe insole. The values of acceleration measured by the sensors are sent via Bluetooth to a smartphone. The localization algorithm implemented on the smartphone, presented here, merges data from the shirt and the shoe to track the steps made by the user and filter out the localization errors caused by movements the shirt and torso. The experimental verification of the algorithm is also presented.
Rocznik
Strony
53--58
Opis fizyczny
Bibliogr. 14 poz., schem., tab., wykr.
Twórcy
  • Lodz University of Technology
autor
  • Lodz University of Technology
  • Lodz University of Technology
Bibliografia
  • [1] Ashkar Rania, Romanovas Michailas, Goridko Vadim, Schwaab Manuel, Traechtler Martin, Manoli Yiannos. „A Low-Cost Shoe-Mounted Inertial Navigation. System with Magnetic Disturbance Compensation”. International Conference on Indoor Positioning and Indoor Navigation. 2013
  • [2] H. Yang, R. Zhang, J. Bordoy, F. Hoflinger, W. Li, C. Schindelhauer, L. Reindl, “Smartphone-Based Indoor Localization System Using Inertial Sensor and Acoustic Transmitter/Receiver”. IEEE Sensors Journal, 2016
  • [3] L. Klingbeil, T. Wark, “A Wireless Sensor Network for Real-Time Indoor Localisation and Motion Monitoring”, 2008 International Conference on Information Processing in Sensor Networks (2008)
  • [4] H. Zou, Z. Chen, H. iang, L. Xie, C. Spanos, “Accurate indoor localization and tracking using mobile phone inertial sensors, WiFi and iBeacon”. 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2017
  • [5] J. Jaekel, M. J. Ahmed, “An inertial navigation system with acoustic obstacle detection for pedestrian applications”. 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2017
  • [6] Y. Nam, “Map-based Indoor People Localization using an Inertial Measurement Unit”, Journal of information science and engineering 27, 1233-1248 (2011)
  • [7] A. Rai, K.K. Chintalapudi, V. N. Padamanabhan, R. Sen, “Zero-effort crowdsourcing for indoor localization”, Mobicom 12 Proceedings of the 18th annual international conference on Mobile computing and networking, 2012, Pages 293-304
  • [8] F. Höflinger, R. Zhang, P. Fehrenbach, J. Bordoy, L. Reindl, C. Schindelhauer. “Localization System based on Handheld Inertial Sensors and UWB”, 2017 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2017
  • [9] H. Liu, H. Darabi, P. Banerjee, J. Liu, “Survey of Wireless Indoor Positioning Techniques and Systems”, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 2007
  • [10] H. Wang, H. Lenz, A. Szabo, J. Bamberger, U. D. Hanebeck, “WLAN-Based Pedestrian Tracking Using Particle Filters and Low-Cost MEMS Sensors”, 4th Workshop on Positioning, Navigation and Communication, 2007
  • [11] Ł. Januszkiewicz, J. Kawecki, R. Kawecki and P. Oleksy, "Wireless indoor positioning system with inertial sensors and infrared beacons," 2016 10th European Conference on Antennas and Propagation (EuCAP), Davos, 2016, pp. 1-3.
  • [12] J. Kawecki, Ł. Januszkiewicz, S. Hausman, „Inercyjny system do lokalizacji ludzi w budynkach wykorzystujący czujniki umieszczone w obuwiu”, Przegląd Telekomunikacyjny Wiadomości Telekomunikacyjne, Gdańsk, 2018, 265-268.
  • [13] Y. Wang, S. Askari, A. M. Shkel, “Study on Mounting Position of IMU for Better Accuracy of ZUPT-Aided Pedestrian Inertial Navigation, 2019 IEEE International Symposium on Inertial Sensors and Systems (INERTIAL), 2019
  • [14] D. Chen, H. Cao, H. Chen, Z. Zhu, X. Qian, W. Xu, M. Huang, “Smart Insole-Based Indoor Localization System for Internet of Things Applications”, IEEE Internet of Things Journal, 2019
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-92c13927-5a26-4dc0-8795-cd5e7932fb98
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