چكيده به لاتين
The problem is that conventional positioning systems work well in outdoor environments and do not respond to the user's exact accuracy inside the building and indoor environments. Due to the existence of this problem and the importance of localization in indoor environments, the thesis explains how to improve positioning in these locations, using a combination of smart Bluetooth low energy technology and smartphone sensors. The proposed methods consist of two parts: the first part is the positioning with the Bluetooth received signal strength indicator. As the received signal is less, the estimated distance has more error. Therefore, the maximum communication radius between the user and the Bluetooth sensor is 7 meters, and in order to ensure the user estimated coordinates, we use the weighted least square method using Mr. Tarrío method and the weighted least square method with considering the diagonal weight matrix and the base sensor change. The second part relates to smartphone sensors that use a magnetometer sensor to determine the user's direction and accelerometer sensor for step counter, speed, and distance traveled by the user. Since in this thesis, the first and second sections are combined to determine the best position of the user, the adaptive strong tracking extended Kalman filter has been used. The results presented in Chapter 4 show that these proposed methods estimate the user's location with an acceptable accuracy.
Keywords: indoor environments, smart Bluetooth low energy, Positioning, Smartphone
