Design of Multiple Spatial Context Detection Method Considering Elongated Top-Bounded Spaces Based on GPS Signal-To-Noise Ratio and Fuzzy Inference

Numerous studies have been conducted on indoor and outdoor seamless positioning and indoor–outdoor detection methods. However, the classification of real space into two types, outdoor space and indoor space, is difficult. One type of space that is difficult to classify is top-bounded space, which can be observed in commercial facilities, logistics facilities, and street-facing sidewalks. In this study, we designed a method for detecting stays in three spatial contexts: Outdoor, top-bounded space, and indoor. This method considers elongated top-bounded spaces covered with a roof and open on one of the sides. Specifically, we selected Global Positioning System (GPS) satellites for stay detection based on the simple extraction of the spatial characteristics of a top-bounded space and designed a decision flow using fuzzy inference based on the signal-to-noise ratio (SNR) of the selected GPS satellites. Moreover, we conducted an evaluation experiment to verify the effectiveness of the proposed method and confirmed that it could correctly detect the stay in three spatial contexts, outdoor, top-bounded space, and indoor, with a high probability of 93.1

Adaptive neuro fuzzy inference system · Algorithm · Bounded function · Computer vision · Fuzzy control system · Fuzzy inference · Fuzzy logic · Geography · Global Positioning System · Spatial contextual awareness · Telecommunications · Computer Science · Evacuation and Crowd Dynamics · Indoor and Outdoor Localization Technologies · Mathematics · Smart Parking Systems Research · Artificial Intelligence

• Spaces in Spatial Science and Urban Applications—State of the Art Review

  Open Access•Sisi Zlatanova, Jinjin Yan et al.•ISPRS International Journal of…•2020

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