Analysis and status quo of smartphone-based indoor localization systems

Subbu, Kalyan Pathapati; Zhang, Chi; Luo, Jun; Vasilakos, Athanasios V.

doi:10.1109/mwc.2014.6882302

Cited by 50 publications

(30 citation statements)

References 15 publications

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“…The SHS seem to be the de facto approach in smart phone based indoor applications [8]. This fact is observed in the recent survey by Subbu et al [9] and applications by Do-Xuan et al [2], Kang et al [8] and Park et al [10].…”

Section: Introductionmentioning

confidence: 86%

Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone

Lakmal

Samarabandu

2016

2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

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Abstract-We present a generalized velocity model to improve localization when using an Inertial Navigation System (INS). This algorithm was applied to correct the velocity of a smart phone based indoor INS system to increase the accuracy by counteracting the accumulation of large drift caused by sensor reading errors. We investigated the accuracy of the algorithm with three different velocity models which were derived from the actual velocity measured at the hip of walking person. Our results show that the proposed method with Gaussian velocity model achieves competitive accuracy with a 50% less variance over Step and Heading approach proving the accuracy and robustness of proposed method. We also investigated the frequency of applying corrections and found that a minimum of 5% corrections per step is sufficient for improved accuracy. The proposed method is applicable in indoor localization and tracking applications based on smart phone where traditional approaches such as GNSS suffers from many issues.

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Section: Introductionmentioning

confidence: 86%

Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone

Lakmal

Samarabandu

2016

2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

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“…An extensive summary of existing works on indoor localization can be found in [29] . The proposed context-aware SON systems will be deployed following the management architecture for positioning-aware SON detailed in [30] .…”

Section: Location Sourcesmentioning

confidence: 99%

Coordinated location-based self-optimization for indoor femtocell networks

2016

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“…For example, Kourogi et al in their classical work integrated self-contained dead-reckoning sensors with GPS and RFID tagged beacons to adjust for positioning errors [8]. A similar but more recent approach can be found in [9], and a good review of indoor INS solutions in [10]. Sometimes, with varied level of success, INS can provide navigation wherever other systems are not available or not applicable.…”

Section: Related Workmentioning

confidence: 99%

Real-time sensor data integration in vertical transport systems: Are conventional mobile devices capable of coping with industrial measurement?

Francik

Brujic-Okretic

Menegazzo

et al. 2016

2016 IEEE Sensors Applications Symposium (SAS)

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Abstract-In this project, mobile connectivity and an innovative approach to sensor data gathering and integration have been employed to automate maintenance inspection, performance monitoring and ride quality measurement in vertical transportation systems. An Inertial Navigation System (INS) has been proposed, implemented and tested to track lift car movement profile. The inherent characteristics of vertical motion have been used to minimize errors and obtain higher accuracy in the integration results. The measurement of a correlation between kinematic profiles constructed from lift-car tracking data compared to its nominal values provides key information on the lift condition at any time. A frequency analysis was applied to processing vibrations and noise data, effectively adding another dimension to the lift ride quality measurement. This approach enabled lift performance profiles to be compiled automatically and transmitted in real time, which significantly rationalized and improved the process of maintenance inspection and monitoring. An advanced prototype, AdInspect, has been produced, with the full set of described features. Industry partners are currently evaluating it.

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Analysis and status quo of smartphone-based indoor localization systems

Cited by 50 publications

References 15 publications

Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone

Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone

Coordinated location-based self-optimization for indoor femtocell networks

Real-time sensor data integration in vertical transport systems: Are conventional mobile devices capable of coping with industrial measurement?

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