INDOOR NAVIGATION
    1.
    发明申请
    INDOOR NAVIGATION 审中-公开

    公开(公告)号:US20190195635A1

    公开(公告)日:2019-06-27

    申请号:US16331493

    申请日:2016-09-07

    IPC分类号: G01C21/20 G01C21/14

    CPC分类号: G01C21/206 G01C21/14

    摘要: In accordance with implementations of the subject matter described herein, a new approach for generating indoor navigation is proposed. Generally speaking, a reference signal that includes time series data collected by at least one environment sensor along a reference path from a start point to a destination is obtained. For example, the reference signal may be obtained by environment sensors equipped in a user's mobile device or another movable entity. Then, a movement event by identifying a pattern from the reference signal, the pattern describing measurements of the at least one environment sensor associated with a specific movement is extracted. Next, a navigation instruction is generated to indicate that the movement event occurs during a movement of the at least one environment sensor along the reference path. Further, the navigation instruction may be provided to a person for indoor navigation.

    ADAPTIVE OBJECT DETECTION
    2.
    发明公开

    公开(公告)号:US20240233311A1

    公开(公告)日:2024-07-11

    申请号:US18562784

    申请日:2021-06-30

    摘要: Implementations of the present disclosure provide a solution for object detection. In this solution, object distribution information and performance metrics are obtained. The object distribution information indicates a size distribution of detected objects in a set of historical images captured by a camera. The performance metric indicates corresponding performance levels of a set of predetermined object detection models. At least one detection plan is further generated based on the object distribution information and the performance metric. The at least one detection plan indicates which of the set of predetermined object detection models is to be applied to each of at least one sub-image in a target image to be captured by the camera. Additionally, the at least one detection plan is provided for object detection on the target image. In this way, a balance between the detection latency and the detection accuracy may be improved.

    ORCHESTRATING EDGE SERVICE WORKLOADS ACROSS EDGE HIERARCHIES

    公开(公告)号:US20220400085A1

    公开(公告)日:2022-12-15

    申请号:US17348701

    申请日:2021-06-15

    IPC分类号: H04L12/911 H04L12/923

    摘要: Computing resources are managed in a computing environment comprising a computing service provider and an edge computing network. The edge computing network comprises computing and storage devices configured to extend computing resources of the computing service provider to remote users of the computing service provider. The edge computing network collects capacity and usage data for computing and network resources at the edge computing network. The capacity and usage data is sent to the computing service provider. Based on the capacity and usage data, the computing service provider, using a cost function, determines a distribution of workloads pertaining to a processing pipeline that has been partitioned into the workloads. The workloads can be executed at the computing service provider or the edge computing network.

    ALLOCATING COMPUTING RESOURCES DURING CONTINUOUS RETRAINING

    公开(公告)号:US20230030499A1

    公开(公告)日:2023-02-02

    申请号:US17948736

    申请日:2022-09-20

    摘要: Examples are disclosed that relate to methods and computing devices for allocating computing resources and selecting hyperparameter configurations during continuous retraining and operation of a machine learning model. In one example, a computing device configured to be located at a network edge between a local network and a cloud service comprises a processor and a memory storing instructions executable by the processor to operate a machine learning model. During a retraining window, a selected portion of a video stream is selected for labeling. At least a portion of a labeled retraining data set is selected for profiling a superset of hyperparameter configurations. For each configuration of the superset of hyperparameter configurations, a profiling test is performed. The profiling test is terminated, and a change in inference accuracy that resulted from the profiling test is extrapolated. Based upon the extrapolated inference accuracies, a set of selected hyperparameter configurations is output.

    MERGING MODELS ON AN EDGE SERVER
    5.
    发明申请

    公开(公告)号:US20220383188A1

    公开(公告)日:2022-12-01

    申请号:US17471816

    申请日:2021-09-10

    IPC分类号: G06N20/00 G06K9/00 G06K9/62

    摘要: Systems and methods are provided for merging models for use in an edge server under the multi-access edge computing environment. In particular, a model merger selects a layer of a model based on a level of memory consumption in the edge server and determines sharable layers based on common properties of the selected layer. The model merger generates a merged model by generating a single instantiation of a layer that corresponds to the sharable layers. A model trainer trains the merged model based on training data for the respective models to attain a level of accuracy of data analytics above a predetermined threshold. The disclosed technology further refreshes the merged model upon observing a level of data drift that exceeds a predetermined threshold. The refreshing of the merged model includes detaching and/or splitting consolidated sharable layers of sub-models in the merged model. By merging models, the disclosed technology reduces memory footprints of models used in the edge server, rectifying memory scarcity issues in the edge server.

    LIVE VIDEO ANALYTICS OVER HIGH FREQUENCY WIRELESS NETWORKS

    公开(公告)号:US20210345222A1

    公开(公告)日:2021-11-04

    申请号:US16862465

    申请日:2020-04-29

    摘要: A multi-hop relay network comprises a set of data nodes arranged in a relay topology, wherein the set of data nodes communicate with one another via a data plane comprising a set of high frequency data links, such as mmWave links. An edge node communicates with one or more of the set of data nodes via the data plane and communicates with the set of data nodes over a control plane comprising a set of low frequency wireless links, such as a Wi-Fi network. The edge node determines a path utilization for the set of high frequency wireless links. When one of the high frequency wireless links is over-utilized, the edge node communicates, to a data node in the set of data nodes via the control plane, a command to change the relay topology. The edge node also determines whether the relay topology is operating at a target accuracy. When it is not, the edge node adjusts a data analytics parameter for a node to improve the overall accuracy of the network.

    INTEGRATING MODEL REUSE WITH MODEL RETRAINING FOR VIDEO ANALYTICS

    公开(公告)号:US20240096063A1

    公开(公告)日:2024-03-21

    申请号:US18078402

    申请日:2022-12-09

    IPC分类号: G06V10/77

    CPC分类号: G06V10/7715 G06V2201/10

    摘要: Systems and methods are provided for reusing and retraining an image recognition model for video analytics. The image recognition model is used for inferring a frame of video data that is captured at edge devices. The edge devices periodically or under predetermined conditions transmits a captured frame of video data to perform inferencing. The disclosed technology is directed to select an image recognition model from a model store for reusing or for retraining. A model selector uses a gating network model to determine ranked candidate models for validation. The validation includes iterations of retraining the image recognition model and stopping the iteration when a rate of improving accuracy by retraining becomes smaller than the previous iteration step. Retraining a model includes generating reference data using a teacher model and retraining the model using the reference data. Integrating reuse and retraining of models enables improvement in accuracy and efficiency.

    DATA STREAMING PROTOCOLS IN EDGE COMPUTING

    公开(公告)号:US20220417306A1

    公开(公告)日:2022-12-29

    申请号:US17362474

    申请日:2021-06-29

    IPC分类号: H04L29/06 H04L12/24 G06N5/04

    摘要: Systems and methods are provided for reducing stream data according to a data streaming protocol under a multi-access edge computing. In particular, an IoT device, such as a video image sensing device, may capture stream data and generate inference data by applying a machine-learning model trained to infer data based on the captured stream data. The inference data represents the captured stream data in a reduced data size based on performing data analytics on the captured data. The IoT device formats the inference data according to the data streaming protocol. In contrast to video data compression, the data streaming protocol includes instructions for transmitting the reduced volume of inference data through a data analytics pipeline.

    INDOOR LOCATION-BASED SERVICE
    10.
    发明申请

    公开(公告)号:US20210190505A1

    公开(公告)日:2021-06-24

    申请号:US17056380

    申请日:2019-06-18

    摘要: In implementations of the subject matter described herein, a solution for providing an indoor location-based service is provided. In this solution, a floor plan about a first floor of a first building comprising at least one floor is obtained. A first map for the first floor is generated based on the floor plan. The first map includes a plurality of vertices and edges, where one vertex corresponds to a position on the first floor, an edge connecting two vertices represents a physical object or a passable path on the first floor, and two positions corresponding to the two vertices are located at the physical object or on the passable path. Moreover, a location-based service is provided to a user at least based on the first map.