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Effective Information Selection Method on Spatiotemporal Information Infrastructure with Photogrammetry

In recent years, there has been an increase in the demand for three-dimensional data of geospatial information in various fields, such as automatic driving and disaster prevention. Beyond5G (above 5th generation network), which features wideband, low latency, reliable connection, allows for the easily collection of spatial information of many points and times from camera-equipped vehicles, such as self-driving cars and drones. Spatiotemporal information at any location and at any time can be provided depending on users’ requests. However, there are instances where the target point’s spatiotemporal information and the request’s target time have not been collected. Therefore, appropriate data completion is required to provide this service seamlessly. To create 3D models using photogrammetry, images are required; therefore, multiple videos that captured the streets near our university were prepared and split into frames. Then, those images were stored in our local storage. The information of the recording date, weather, file path to the image, and location (latitude and longitude) were saved to our database per frame. When users request spatiotemporal information, this system commences searching for images that meet the requirements. When the number of matched images are sufficient, the 3D model is created. When it is insufficient, the data are complemented appropriately.