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From one to crowd: a survey on crowdsourcing-based wireless indoor localization

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Abstract

Wireless indoor localization has attracted growing research interest in the mobile computing community for the last decade. Various available indoor signals, including radio frequency, ambient, visual, and motion signals, are extensively exploited for location estimation in indoor environments. The physical measurements of these signals, however, are still limited by both the resolution of devices and the spatial-temporal variability of the signals. One type of noisy signal complemented by another type of signal can benefit the wireless indoor localization in many ways, since these signals are related in their physics and independent in noise. In this article, we survey the new trend of integrating multiple chaotic signals to facilitate the creation of a crowd-sourced localization system. Specifically, we first present a three-layer framework for crowdsourcing-based indoor localization by integrating-multiple signals, and illustrate the basic methodology for making use of the available signals. Next, we study the mainstream signals involved in indoor localization approaches in terms of their characteristics and typical usages. Furthermore, considering multiple different outputs from different signals, we present significant insights to integrate them together, to achieve localizability in different scenarios.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments. This work was partly supported by the National Natural Science Foundation of China (Grant No. 61422214), National Basic Research Program (973 program) (2014CB347800), the Program for New Century Excellent Talents in University, the Hunan Provincial Natural Science Fund for Distinguished Young Scholars (2016JJ1002), and the Research Funding of NUDT (JQ14-05-02 and ZDYYJCYJ20140601).

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Authors and Affiliations

  1. Nanjing Telecommunication Technology Research Institute, National University of Defense Technology, Nanjing, 210089, China

    Xiaolei Zhou

  2. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha, 410073, China

    Xiaolei Zhou, Tao Chen, Deke Guo, Xiaoqiang Teng & Bo Yuan

Authors
  1. Xiaolei Zhou
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  2. Tao Chen
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  3. Deke Guo
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  4. Xiaoqiang Teng
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  5. Bo Yuan
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Corresponding author

Correspondence to Deke Guo.

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Xiaolei Zhou received the BA degree from Nanjing University, China in 2009, and the MS and PhD degrees in military operational research from National University of Defense Technology (NUDT), China in 2011 and 2016, receptively. He is currently an assistant professor with the Nanjing Telecommunication Technology Research Institute, NUDT. His research interests include mobile and pervasive computing, mobile crowdsensing, especially wireless indoor positioning and location based services.

Tao Chen received the BS degree in military science, the MS and PhD degrees in military operational research from the National University of Defense Technology (NUDT), China in 2004, 2006, and 2011, respectively. He is an assistant professor with the College of Information System and Management, NUDT. His research interests include wireless sensor networks, peer-to-peer computing, and data center networking.

Deke Guo received the BS degree in industry engineering from Beijing University of Aeronautic and Astronautic, China in 2001, and the PhD degree in management science and engineering from National University of Defense Technology (NUDT), China in 2008. He is a professor with the College of Information System and Management, NUDT. His research interests include distributed systems, softwaredefined networking, data center networking. He is a member of the ACMand the IEEE. He is an awardee of the NSFC Excellent Young Scholars Program in 2014.

Xiaoqiang Teng received the BS degree from the School of Mechanical Engineering, Shenyang University of Technology, China in 2013. Currently, he is a PhD student in the College of Information System and Management, National University of Defense Technology, China. His research interests include mobile computing, pervasive computing, and computer vision.

Bo Yuan received the BS degree from the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, China in 2015. Currently, he is a master student in the College of Information System and Management, National University of Defense Technology, China. His research interests include mobile computing, pervasive computing, and computer vision.

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Zhou, X., Chen, T., Guo, D. et al. From one to crowd: a survey on crowdsourcing-based wireless indoor localization. Front. Comput. Sci. 12, 423–450 (2018). https://doi.org/10.1007/s11704-017-6520-z

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