Wifi fingerprinting indoor positioning with multiple access points in a single base station using probabilistic method

Mazlan, M.A.A.A. and Khir, M.H.M. and Saad, N.M. and Dass, S.C. (2017) Wifi fingerprinting indoor positioning with multiple access points in a single base station using probabilistic method. International Journal of Applied Engineering Research, 12 (6). p. 1102.

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Abstract

WiFi fingerprinting for indoor positioning is well known as one of the most efficient techniques to estimate indoor target location. This method requires a training phase to collect Receiving Signal Strength (RSS) samples that will be utilized in location estimation phase using matching algorithms. Recently, most commercially indoor positioning solutions used on smartphone utilizes the current building infrastructure to estimate personnel location where wireless router is used as an Access Point (AP) in each base station to extract the RSS values. However, for buildings with inadequate infrastructure setup, implementing multiple base stations using a single AP in each base station would require an exhaustive cost of manpower and time especially for a small scale positioning setup. There are also not enough distinct RSS values at each location covered by a single base station. Thus, WiFi fingerprinting using multiple APs with omnidirectional and directional antennas in a single base station employing a probabilistic approach has been proposed to minimize the infrastructure setup. Based on experimental results, the proposed multiple APs in a single base station was found to reduce the number of base stations required to achieve the same or better accuracy as existing approach using the same number of APs. Findings also demonstrated feasibility of using the proposed multiple APs in a single base station instead of single AP in a single base station at different locations in WiFi fingerprinting indoor positioning. © Research India Publications.

Item Type: Article
Impact Factor: cited By 0
Departments / MOR / COE: Division > Academic > Faculty of Engineering > Electrical & Electronic Engineering
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Apr 2018 07:28
Last Modified: 20 Apr 2018 07:28
URI: http://scholars.utp.edu.my/id/eprint/19672

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