This article presents an indoor positioning algorithm using accelerometer, gyroscope, and magnetic sensors to determine the location of travel users, to provide location-based services for users on intelligent travel guide systems. | Journal of Science & Technology 128 (2018) 014-019 A Sensor-based Indoor Positioning Algorithm for Smart-Tour Applications Vinh Tran-Quang*, Phung Dinh Phuc Hanoi University of Science and Technology – No. 1, Dai Co Viet Str., Hai Ba Trung, Ha Noi, Viet Nam Received: May 29, 2018; Accepted: June 29, 2018 Abstract This article presents an indoor positioning algorithm using accelerometer, gyroscope, and magnetic sensors to determine the location of travel users, to provide location-based services for users on intelligent travel guide systems. The main contributions of the proposal method on this paper are the application of a Kalman filter to eliminate interference of sensor signals that are received from integrated sensors on common smartphones, to handle the time velocity drift when user moving smartphone while standing in place, and therefore, to increase the positioning accuracy. The experiment results show that the proposed positioning algorithm achieves decimeter accuracy in indoor environment, which is suitable for positioning applications such as smart-tour applications. Keywords: Indoor Positioning Algorithm, Location-based Services, Kalman Filter 1. Introduction . Gyroscope Sensor The*most common and widespread positioning method today is the Global Positioning System (GPS). Unfortunately, GPS is not an effective way for positioning in indoor environments such as inside buildings or underground works. Sensor-based indoor positing techniques can be used for applications which require high accuracy in indoor environments such as automated travel guides, navigation in the shopping center. In this article, we propose and develop an indoor positioning algorithm that exploited three types of basic sensors integrated in common smartphones: accelerometer, gyroscope, and magnetic sensors to determine the location of travel users. To achieve accuracy requrement in a sensor-based indoor positioning, it is necessary to solve some problems such as eliminating the
