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Author: search.filters.author.Wongwirat, OlarnSubject: search.filters.subject.Wi-Fi

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    Enhancing Wi-Fi-based Fingerprint Technique for Indoor Positioning System
    (2024-01-01)
    Nimnaul, Tanapol
    ;
    Bureetes, Natchapong
    ;
    Siriwat, Siwat
    ;
    Wongwirat, Olarn
    This paper addresses the enhancement of the Wi-Fi-based fingerprint technique for an indoor positioning system applied in an experimental area. The conventional Wi-Fi-based fingerprint technique utilizes a k-nearest neighbor (k-NN) algorithm for position estimation. The k-NN algorithm is a simple and intuitive classification algorithm based on distance metric, i.e., Euclidean distance (ED), but often demonstrates limited accuracy. To mitigate this constraint and enhance positioning precision, advanced machine learning algorithms in artificial neural networks (ANNs) have been introduced. Although ANN algorithms are considered highly reliable, they are complex and resource-intensive algorithms, resulting in less suitable for a small-scale area that requires simple indoor positioning applications. In contrast, the random forest (RF) algorithm offers comparable positioning accuracy while being more computationally efficient, making it a favorable choice for such scenarios. The work in this paper enhances the accuracy of the Wi-Fi-based fingerprint technique for indoor positioning systems by adopting the RF algorithm over the k-NN alternative for position estimation accuracy. The number of received signal strength (RSS) data selected from appropriate access points (APs) in the area chosen by a feature selection method is a pivotal factor influencing accuracy improvements. The experimental results express the direct correlation between increased RSS data and accuracy improvement for both algorithms. Significantly, the application of the feature selection method using the information gain ratio augments the positioning accuracy specifically for the RF algorithm.
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    An experimental study of wi-fi access service using drones in container yard
    (2020-10-13)
    Meesriyong, Krongpon
    ;
    Wongwirat, Olarn
    ;
    Namuduri, Kamesh
    Currently, there are some restrictions on employees to access the network in the area of the container yard. This is not only because the operating computers are installed at the positions that are quite remote from the working areas in the container yard but also there is no wireless access network, or Wi-Fi, provided. Installing a fixed tower to transmit a radio signal providing the Wi-Fi access service is also not applicable in the container yard since the layout of placing containers is often changed periodically. Furthermore, the containers are made by metal and often stacked over that causes blocking of the radio signal resulting in a dead zone occurred in several spots in the area. Therefore, the work in this paper presents an experimental study for assessing feasibility to provide the Wi-Fi access service by using drones in the container yard. A business analysis, site survey, and prototype design are performed in the study. Then, the received signal strength, coverage area, and support data rate are defined as parameters to be measured in accordance with the drone altitudes in the experiments. Finally, the results verification and analysis are conducted for affirming the feasibility to use drones for providing the Wi-Fi access service in the container yard in the future.