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Autonomous Landmark Calibration Method for Indoor Localization

Department of Industrial Engineering, Ajou University, Suwon 16499, Korea
Infrastructure Protection Team, Korea Internet and Security Agency, Seoul 05717, Korea
Author to whom correspondence should be addressed.
Sensors 2017, 17(9), 1952;
Received: 21 June 2017 / Revised: 27 July 2017 / Accepted: 21 August 2017 / Published: 24 August 2017
(This article belongs to the Special Issue Mobile Sensing Applications)
PDF [6247 KB, uploaded 24 August 2017]


Machine-generated data expansion is a global phenomenon in recent Internet services. The proliferation of mobile communication and smart devices has increased the utilization of machine-generated data significantly. One of the most promising applications of machine-generated data is the estimation of the location of smart devices. The motion sensors integrated into smart devices generate continuous data that can be used to estimate the location of pedestrians in an indoor environment. We focus on the estimation of the accurate location of smart devices by determining the landmarks appropriately for location error calibration. In the motion sensor-based location estimation, the proposed threshold control method determines valid landmarks in real time to avoid the accumulation of errors. A statistical method analyzes the acquired motion sensor data and proposes a valid landmark for every movement of the smart devices. Motion sensor data used in the testbed are collected from the actual measurements taken throughout a commercial building to demonstrate the practical usefulness of the proposed method. View Full-Text
Keywords: location-based services; data analytics; landmark; dead reckoning location-based services; data analytics; landmark; dead reckoning

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Kim, J.-H.; Kim, B.-S. Autonomous Landmark Calibration Method for Indoor Localization. Sensors 2017, 17, 1952.

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