Journal ArticleDOI
A Survey of Selected Indoor Positioning Methods for Smartphones
Pavel Davidson,Robert Piche +1 more
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TLDR
Methods for step counting, step length and direction estimation, orientation tracking, motion classification, transit mode detection, and floor change detection in multi-storey buildings are discussed.Abstract:
This paper provides an overview of the most significant existing methods for indoor positioning on a contemporary smartphone. The approaches include Wi-Fi and Bluetooth based positioning, magnetic field fingerprinting, map aided navigation using building floor plans, and aiding from self-contained sensors. Wi-Fi and Bluetooth based positioning methods considered in this survey are fingerprint approaches that determine a user's position using a database of radio signal strength measurements that were collected earlier at known locations. Magnetic field fingerprinting can be used in an information fusion algorithm to improve positioning. The map-matching algorithms include application of wall constraints, topological indoor maps, and building geometry for heading correction. Finally, methods for step counting, step length and direction estimation, orientation tracking, motion classification, transit mode detection, and floor change detection in multi-storey buildings are discussed.read more
Citations
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A Survey of Indoor Localization Systems and Technologies
TL;DR: This paper aims to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time ofFlight (RTOF), and received signal strength (RSS) based on technologies that have been proposed in the literature.
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Deep Learning in Mobile and Wireless Networking: A Survey
TL;DR: This paper bridges the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas, and provides an encyclopedic review of mobile and Wireless networking research based on deep learning, which is categorize by different domains.
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A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation
TL;DR: This survey provides a comprehensive review of cellular localization systems including recent results on 5G localization, and solutions based on wireless local area networks, highlighting those that are capable of computing 3D location in multi-floor indoor environments.
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Deep Learning in Mobile and Wireless Networking: A Survey
TL;DR: In this article, the authors provide an encyclopedic review of mobile and wireless networking research based on deep learning, which they categorize by different domains and discuss how to tailor deep learning to mobile environments.
Journal ArticleDOI
Robustness, Security and Privacy in Location-Based Services for Future IoT: A Survey
Liang Chen,Sarang Thombre,Kimmo Järvinen,Elena Simona Lohan,Anette Alen-Savikko,Helena Leppäkoski,M. Zahidul H. Bhuiyan,Shakila Bu-Pasha,Giorgia Ferrara,Salomon Honkala,Jenna Lindqvist,Laura Ruotsalainen,Päivi Korpisaari,Heidi Kuusniemi +13 more
TL;DR: This survey paper addresses a broad range of security and privacy aspects in IoT-based positioning and localization from both technical and legal points of view and aims to give insight and recommendations for future IoT systems providing more robust, secure, and privacy-preserving location-based services.
References
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Journal ArticleDOI
Survey of Wireless Indoor Positioning Techniques and Systems
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Book ChapterDOI
Activity recognition from user-annotated acceleration data
Ling Bao,Stephen S. Intille +1 more
TL;DR: This is the first work to investigate performance of recognition algorithms with multiple, wire-free accelerometers on 20 activities using datasets annotated by the subjects themselves, and suggests that multiple accelerometers aid in recognition.
Journal ArticleDOI
A Survey on Human Activity Recognition using Wearable Sensors
Oscar D. Lara,Miguel A. Labrador +1 more
TL;DR: The state of the art in HAR based on wearable sensors is surveyed and a two-level taxonomy in accordance to the learning approach and the response time is proposed.
Proceedings ArticleDOI
The Horus WLAN location determination system
TL;DR: The Horus system identifies different causes for the wireless channel variations and addresses them and uses location-clustering techniques to reduce the computational requirements of the algorithm and the lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.