SATELLITE COMMUNICATION WITH DISTRIBUTED GROUND STATIONS USING A MULTI-LEVEL QUEUE

    公开(公告)号:US20230179288A1

    公开(公告)日:2023-06-08

    申请号:US17714934

    申请日:2022-04-06

    CPC classification number: H04B7/18513 H04B7/155 H04B7/18584

    Abstract: The disclosure herein describes using satellites and ground sinks and/or stations for routing IoT device data packets from IoT devices. A target ground sink in range of the satellite is identified and an expected reception (ER) score for the target ground sink is calculated based on ER parameter data and location data of the satellite. A data packet in a first level of a multi-level data structure of the satellite is sent to the target ground sink and, based on an ER threshold exceeding the ER score, the packet is moved to a second level of the multi-level data structure, whereby the data packet is queued to be sent to another ground sink. The disclosure further includes using cell towers as ground sinks and/or using them for backhauling with other ground sinks. The flexibility of the disclosure enables large ground sink networks to be established, reducing latency of packet routing.

    Geospatial Image Processing for Targeted Data Acquisition

    公开(公告)号:US20220375031A1

    公开(公告)日:2022-11-24

    申请号:US17323358

    申请日:2021-05-18

    Abstract: A computer implemented method includes obtaining data for raw image frames captured by a moving camera. The raw image frames are indexed geographically, and a graph is created from the multiple raw image frames. The graph includes image frames as vertices and edges that represent image frames having overlapping image information. The method further includes skipping frames based on the amount of overlap, determining a frame having an interesting feature, using the graph to find additional raw image frames that have the interesting feature, combining multiple raw image frames to form a unique image frame, and transmitting the unique image frame.

    CONTROLLING ASYNCHRONOUS FUSION OF SPATIO-TEMPORAL MULTIMODAL DATA

    公开(公告)号:US20220327335A1

    公开(公告)日:2022-10-13

    申请号:US17219822

    申请日:2021-03-31

    Abstract: A system for fusion of multimodal receives a spatial input and a temporal input, wherein the spatial input comprises spatial data having spatial embeddings and the temporal input comprises temporal data having temporal embeddings. The spatial embeddings and the temporal embeddings have different time dimensions. A spatial data output with the spatial embeddings having a same time dimension as the temporal embeddings is generated from the spatial data based on a spatial perception model. The spatial perception model is pre-trained. A temporal data output is generated from the temporal data based on a temporal model. The spatial data output and the temporal data output are combined into an output representing dependencies between the spatial input and the temporal input using a fusion model. A desired target variable is obtained from the output and one of an estimated or predicted value is generated based on the desired target value.

    IMAGE DATA SEGMENTATION AND TRANSMISSION

    公开(公告)号:US20210136171A1

    公开(公告)日:2021-05-06

    申请号:US16746105

    申请日:2020-01-17

    Abstract: A computing device is provided, including a logic subsystem with one or more processors, and memory storing instructions executable by the logic subsystem. These instructions are executed to obtain one or more source images, segment the one or more source images to generate a plurality of segments, determine a priority order for the plurality of segments, and transmit the plurality of segments to a remote computing device in the priority order. The plurality of segments are spatial components generated by spatial decomposition of the one or more source images and/or frequency components that are generated by frequency decomposition of the one or more source images. A remote computing device may receive these components in priority order, and perform certain algorithms on individual components without waiting for the entire image to upload.

    RECOVERING OCCLUDED IMAGE DATA USING MACHINE LEARNING

    公开(公告)号:US20210133936A1

    公开(公告)日:2021-05-06

    申请号:US16786257

    申请日:2020-02-10

    Abstract: Examples disclosed herein are related to using a machine learning model to generate image data. One example provides a system, comprising one or more processors, and storage comprising instructions executable by the one or more processors to obtain image data comprising an image with unoccluded features, apply a mask to the unoccluded features in the image to form partial observation training data comprising a masked region that obscures at least a portion of the unoccluded features, and train a machine learning model comprising a generator and a discriminator at least in part by generating image data for the masked region and comparing the image data generated for the masked region to the image with unoccluded features.

Patent Agency Ranking