APPLICATION-IN-A-BOX FOR DEPLOYMENT AND SELF-OPTIMIZATION OF REMOTE APPLICATIONS

    公开(公告)号:US20240314531A1

    公开(公告)日:2024-09-19

    申请号:US18605105

    申请日:2024-03-14

    CPC classification number: H04W4/50 H04W24/02 H04W72/52

    Abstract: Systems and methods are provided for deploying applications within a wireless network infrastructure, including initiating, by a centralized control module in a pre-configured hardware unit having a 5G wireless communication module, edge computing device, centralized control module, and data processing module with access to cloud resources, a setup procedure upon receiving a deployment command, the setup procedure including activating the 5G wireless communication module to establish a network connection. User equipment for communication with sensors and cameras is deployed using an edge device through the network connection. Application deployment is managed using a centralized control module including an edge cloud optimizer for allocating resources between an edge computing device and the cloud resources based on real-time analysis of network conditions and application requirements. Computing resource allocation between the edge computing device and cloud resources is dynamically adjusted for application requirements and network conditions during automated application deployment and optimization.

    REINFORCEMENT-LEARNING BASED SYSTEM FOR CAMERA PARAMETER TUNING TO IMPROVE ANALYTICS

    公开(公告)号:US20220414935A1

    公开(公告)日:2022-12-29

    申请号:US17825519

    申请日:2022-05-26

    Abstract: A method for automatically adjusting camera parameters to improve video analytics accuracy during continuously changing environmental conditions is presented. The method includes capturing a video stream from a plurality of cameras, performing video analytics tasks on the video stream, the video analytics tasks defined as analytics units (AUs), applying image processing to the video stream to obtain processed frames, filtering the processed frames through a filter to discard low-quality frames and dynamically fine-tuning parameters of the plurality of cameras. The fine-tuning includes passing the filtered frames to an AU-specific proxy quality evaluator, employing State-Action-Reward-State-Action (SARSA) reinforcement learning (RL) computations to automatically fine-tune the parameters of the plurality of cameras, and based on the reinforcement computations, applying a new policy for an agent to take actions and learn to maximize a reward.

    Tracking within and across facilities

    公开(公告)号:US11468576B2

    公开(公告)日:2022-10-11

    申请号:US17178570

    申请日:2021-02-18

    Abstract: A method for tracing individuals through physical spaces that includes registering cameras in groupings relating a physical space. The method further includes performing local video monitoring including a video sensor input that outputs frames from inputs from recording with the cameras in the groupings, a face detection application for extracting faces from the output frames, and a face matching application for matching faces extracted from the output frames to a watchlist, and a local movement monitor that assigns tracks to the matched faces. The method further includes performing a global monitor including a biometrics monitor for preparing the watchlist of faces, the watchlist of faces being updated when a new face is detected by the cameras in the groupings, and a global movement monitor that combines the outputs from the assigned tracks to the matched faces to launch a report regarding individual population traveling to the physical spaces.

    Usecase specification and runtime execution

    公开(公告)号:US11249803B2

    公开(公告)日:2022-02-15

    申请号:US16809154

    申请日:2020-03-04

    Abstract: A computer-implemented method includes obtaining a usecase specification and a usecase runtime specification corresponding to the usecase. The usecase includes a plurality of applications each being associated with a micro-service providing a corresponding functionality within the usecase for performing a task. The method further includes determining that at least one instance of the at least one of the plurality of applications can be reused during execution of the usecase based on the usecase specification and the usecase runtime specification, and reusing the at least one instance during execution of the usecase.

    MULTI-FACTOR AUTHENTICATION FOR PHYSICAL ACCESS CONTROL

    公开(公告)号:US20200294339A1

    公开(公告)日:2020-09-17

    申请号:US16809147

    申请日:2020-03-04

    Abstract: Methods and systems for authentication include determining, at a first worker system, that a master system that stores a current authentication-list cannot be reached by a first network. Authentication is performed on an authentication request using a previously stored copy of the authentication-list at the first worker system. The authentication includes facial recognition that is performed on detected face images for a first time window, before receiving the authentication request, and for a second time window, after receiving the authentication request. Authentication removes matching detected face images after completing an authentication request to prevent other individuals from using a same identifier. Access is granted to a secured area responsive to the authentication.

    WiFi-based indoor positioning and navigation as a new mode in multimodal transit applications

    公开(公告)号:US09970776B2

    公开(公告)日:2018-05-15

    申请号:US15088352

    申请日:2016-04-01

    CPC classification number: G01C21/3423

    Abstract: A system for planning a trip includes heterogeneous data sources including map data, traffic information, vehicle trace data, weather reports, social media data, commuter feedback data, GIS data, travel time data; a stream analytics engine coupled to the heterogeneous data sources; a batch analytics engine coupled to the heterogeneous data sources; and a multi-modal journey planner coupled to the stream analytics engine and the batch analytics engine, the multi-modal journey planner processing indoor travel information and providing real-time updates while a journey is under progress, the multi-modal journey planner providing a journey time forecast as the journey time reflects indoor travel time.

    Resource orchestration for microservices-based 5G applications

    公开(公告)号:US12159168B2

    公开(公告)日:2024-12-03

    申请号:US17863685

    申请日:2022-07-13

    Abstract: A method for performing resource orchestration for microservices-based 5G applications in a dynamic, heterogenous, multi-tiered compute and network environment is presented. The method includes managing compute requirements and network requirements of a microservices-based application jointly by positioning computing nodes distributed across multiple layers, across edges and at a central cloud, identifying and modeling coupling relationships between compute and network resources for a plurality of microservices, when only application-level requirements are provided, to build coupling functions, solving a multi-objective optimization problem to identify how each of the plurality of microservices are deployed in the dynamic, heterogenous, multi-tiered compute and network environment by employing the coupling functions to jointly optimize resource usage of the compute and network resources across different compute and network slices, and deriving optimal joint network and compute resource allocation and function placement decisions.

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