Abstract
Indoor Positioning System (IPS) in generally perform as a network of devices that always located the objects or people inside a building wirelessly. An IPS has direction relies nearby anchors and also can be entirely local to your smartphone. With the rapid growth and sharp increase in Indoor Positioning System (IPS) demand in the world, there are a lot of researchers trying to invent new algorithm to develop IPS. This paper proposed the Bluetooth-Base Indoor Positioning Algorithm. The RF characteristics such as RSSI and WLAN RSSI fingerprinting system normally formed by two phases, fist is offline phase and second is online phase. Fingerprinting system handling both off-line and online data and estimate the user’s location. Our algorithm design is a collection of Weighted K-Nearest Neighbors (WKNN) and Filtering algorithms by KALMAN Filter. Finally, to avoid the problems of IPS and get a better accurate we proposed two algorithms: Weighted K-Nearest Neighbors Particle Filter (WKNNPF) and Weighted K-Nearest Neighbors Extended Kalman Filter (WKNNEKF) compare to KNN and WKNN result. After comparing we found that the result of WKNNPF and WKNNEKF is better result than KNN and WKNN. The Probability in 3M of WKNN is about 79%, WKNNEKF is about 89%, and WKNNPF is about 95.1%. Among one of the proposed algorithms WKNNPF is better than WKNNEKF on accuracy 1.7-2 meters with 42.2m/s response time.
Highlights
In present, indoor positioning system became more interested and more advantages for the people in the world
We found that the accurate point of Weighted K-Nearest Neighbors (WKNN) algorithm is bigger than Weighted KNearest Neighbors Extended Kalman Filter (WKNNEKF) and Weighted KNearest Neighbors Particle Filter (WKNNPF) algorithm, and the accurate point of WKNNEKF algorithm is smaller than WKNN and bigger than WKNNPF
Red stand for WKNN algorithm, green stand for WKNNEKF algorithm and blue stand for WKNNPF
Summary
Indoor positioning system became more interested and more advantages for the people in the world. Many applications that we have seen some papers introduced in field of m-commerce that based on the principle of the wellestimated location of the various customer as well as in wireless network sector. For example here, it is talking about advertising in large stores or guides in museums which using modern portable devices is possible, in case if we estimate the exact location of a mobile terminal in every single time. The totally proposed ideas of this paper was notice about the challenge with all of the issues faced in location estimation plus with the general evaluation criteria which focus on a Bluetooth-based indoor positioning system as well. The system developed as usual and it’s based on a well-known and well-publicized of the triangular method by using the theoretical of received signal strength of the surrounding environment of the Bluetooth access point we have
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