1. Technical Field
The present disclosure relates to an indoor positioning system, and more particularly, to an indoor positioning system based on geomagnetic signal positioning technology in combination with computer vision positioning technology.
2. Description of Related Art
As the development of internet of things (IoT) applications has gradually matured, Online to Offline (O2O) business model has become a booming industry. As a result, indoor positioning technology is developed to provide O2O more options with new combination of strategies.
Most of the current indoor positioning technology is based and build upon hardware equipment, such as the existing Becon or WiFi positioning, which utilize the signal strength between the hardware equipment and obtain the current position of the moving device via the calculation of triangulation positioning. However, in order to achieve the effect of accurate positioning, current Beacon or WiFi positioning technology both require a large amount of bluetooth nodes or increased number of WiFi routers. It is inevitable that the initial cost for construction is rather high as a result of high demand for hardware, let alone the maintenance and upgrading cost and technical problems that will be faced for operation.
In order to reduce the hardware equipment cost, computer vision positioning and geomagnetic signal positioning are current technologies. Current computer vision positioning features Visual-Inertial Odometry (VIO) and camera lens to record the indoor image and spatial coordinate system to generate indoor image data which is matched with the image created during map generating to capture the coordinate values, thereby achieving the goal of positioning. However, the indoor positioning image data may become too big when the field to be positioned is large. This will occupy a lot of CPUs' computation and thus slows down the operation and thereby affecting the comparing time.
On the other hand, geomagnetic signal positioning uses geomagnetic signals for indoor positioning. When the indoor image data is constructed, both the geomagnetic signals and coordinate system of the indoor space will be recorded at the same time to generate a final geomagnetic indoor image data. However, as the geomagnetic is a wave signal that will have slight fluctuations in different time, the relative relations of the signal remain constant. Therefore, in the user mode, when the user has a position shift, the repositioning can be done via algorithm. However, when the field is too big, convergence time will take longer, i.e., the user is required to travel for longer distance for effective positioning.
From the above, it is clear that there are drawbacks of the current indoor positioning technology. In view of these drawbacks arise from the current technology, the inventor of the present disclosure successfully develops an indoor positioning system based on geomagnetic signal in combination with computer vision.