Fuzzy-based Wi-Fi localisation with high accuracy using fingerprinting

Abstract

In this paper, a localisation system based on Wi-Fi fingerprinting and fuzzy data analysis is presented. Three localisation techniques were used, Euclidean distance, K-nearest neighbours (KNN), and weighted K-nearest neighbours (WKNN), to get three independent estimations of a user's location. Then fuzzy analysis is used to combine the three estimates to achieve highly-accurate localisation. Two experiments were conducted in order to test the proposed new technique and compare it to the traditional fingerprinting techniques present in the literature. The results of the experiments proved that the proposed technique outperforms the traditional techniques.

Analytic hierarchy process-based model reduction of higher order continuous systems using sine cosine algorithm

“…This approach can be investigated for other systems having more objectives. Additionally, neural network, fuzzy logic (Ibrahim et al, 2018;Qureshi et al, 2018;Sun et al, 2011;Massou and Boumhidi, 2017) or other optimisation techniques (Kumar and Narayan, 2017;Katal and Narayan, 2017;Singh et al, 2017b) can also be used for model order reduction.…”

Designing and developing a mobile application for indoor real-time positioning and navigation in healthcare facilities

“…However, WiFi-based positioning is characterized by low accuracy (about 3–5 metres) that involves the use of many wireless access points (WAPs) so that the actual coverage can be increased. Furthermore, the implementation of APIs (Application Programming Interface) for indoor location by using the WiFi interface is not allowed for iOS devices, as Apple Inc. has stopped building and publishing APIs related to the detection of the power of the signal through the APs (Access Points) [ 19 ]. Bluetooth Low Energy beacons (BLE beacons): hardware transmitters that broadcast their identifier to nearby portable electronic devices.…”