 This paper proposes a new 3D indoor localization framework called 3D WBQM which combines multiple technologies such as Wi-Fi, Bluetooth low energy, BLE, quick response, QR per code, microelectromechanical system, MEMS as sensors, and robust unscented Kalman filter, RUKF, to accurately locate people inside buildings. The framework utilizes the integration of these technologies to provide accurate positioning in large scale indoor areas. It also employs inertial odometry to estimate the location of pedestrians, and then combines this with the other technologies to further improve the accuracy of the positioning. Additionally, the framework uses RUKF to combine the estimated locations from all the technologies to achieve high precision positioning. The experimental results show that the proposed 3D WBQM framework is able to achieve meter level positioning accuracy in Wi-Fi fine time measurement, FTM, supported areas. This article was authored by Yu Yu, Yi Zhang, Liang Chen, and others.