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A STUDY ON GENERATION METHODOLOGY OF AN INDOOR NETWORK USING BUILDING EVACUATION MAP
Abstract
The demand for an indoor navigation service is increasing as indoor positioning technology is developed, therefore it is necessary to construct indoor network data that can be directly used for navigation. In this study, indoor network data were constructed using indoor evacuation map images, which can be easily obtained. The evacuation route in the map can be used as network information because it represents the connection between each room as well as the connection between room entrances and the main entrance of the floor. The indoor network defined in this study is composed of nodes of entrance and links indicating the connections between entrances. A conditional generative adversarial network (GAN) was used to extract information about door locations and evacuation routes from the evacuation map images, and door locations were converted into point data. Through vector conversion, evacuation route information was saved as polyline data. The generated door points and evacuation route lines were overlaid with the existing indoor wall data to generate network data for each floor. Through the proposed method, it is possible to generate network data that can be directly used for a navigation service by using the existing building evacuation information constructed already. It is expected that the indoor network data will be automatically generated through a large amount of image data that can be easily obtained by utilizing research results.
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