Abstract:
A method for free flow fever screening is presented. The method includes capturing a plurality of frames from thermal data streams and visual data streams related to a same scene to define thermal data frames and visual data frames, detecting and tracking a plurality of individuals moving in a free-flow setting within the visual data frames, and generating a tracking identification for each individual of the plurality of individuals present in a field-of-view of the one or more cameras across several frames of the plurality of frames. The method further includes fusing the thermal data frames and the visual data frames, measuring, by a fever-screener, a temperature of each individual of the plurality of individuals within and across the plurality of frames derived from the thermal data streams and the visual data streams, and generating a notification when a temperature of an individual exceeds a predetermined threshold temperature.
Abstract:
Systems and methods are provided for dynamically tuning camera parameters in a video analytics system to optimize analytics accuracy. A camera captures a current scene, and optimal camera parameter settings are learned and identified for the current scene using a Reinforcement Learning (RL) engine. The learning includes defining a state within the RL engine as a tuple of two vectors: a first representing current camera parameter values and a second representing measured values of frames of the current scene. Quality of frames is estimated using a quality estimator, and camera parameters are adjusted based on the quality estimator and the RL engine for optimization. Effectiveness of tuning is determined using perceptual Image Quality Assessment (IQA) to quantify a quality measure. Camera parameters are adaptively tuned in real-time based on learned optimal camera parameter settings, state, quality measure, and set of actions, to optimize the analytics accuracy for video analytics tasks.
Abstract:
Methods and systems for executing an application include extending a container orchestration system application programming interface (API) to handle objects that specify components of an application. An application representation is executed using the extended container orchestration system API, including the instantiation of one or more services that define a data stream path from a sensor to a device.
Abstract:
A method for specifying and executing an application including multiple microservices on 5G slices within a multi-tiered 5G infrastructure is presented. The method includes managing compute requirements and network requirements of the application simultaneously by determining end-to-end application characteristics by employing an application slice specification including an application ID component, an application name component, an application metadata component, a function dependencies component, a function instances component, and an instance connections component, specifying a function slice specification including a function network slice specification and a function compute slice specification, and employing a runtime component including a resource manager, an application slice controller, and an application slice monitor, wherein the resource manager maintains a database and manages starting, stopping, updating, and deleting application instances.
Abstract:
A method for free flow fever screening is presented. The method includes capturing a plurality of frames from thermal data streams and visual data streams related to a same scene to define thermal data frames and visual data frames, detecting and tracking a plurality of individuals moving in a free-flow setting within the visual data frames, and generating a tracking identification for each individual of the plurality of individuals present in a field-of-view of the one or more cameras across several frames of the plurality of frames. The method further includes fusing the thermal data frames and the visual data frames, measuring, by a fever-screener, a temperature of each individual of the plurality of individuals within and across the plurality of frames derived from the thermal data streams and the visual data streams, and generating a notification when a temperature of an individual exceeds a predetermined threshold temperature.
Abstract:
Methods and systems for deploying a video analytics system include determining one or more applications for a security system in an environment, including one or more constraints. Each functional module in a directed graph representation of one or more applications is profiled to generate one or more configurations for each functional module. The nodes of each graph representation represent functional modules of the respective application, and repeated module configurations are skipped. Resource usage for each of the one or more applications is estimated using the one or more configurations of each functional module and the one or more constraints. The one or more applications are deployed in the environment.
Abstract:
A method is disclosed to manage a multi-processor system with one or more manycore devices, by managing real-time bag-of-tasks applications for a cluster, wherein each task runs on a single server node, and uses the offload programming model, and wherein each task has a deadline and three specific resource requirements: total processing time, a certain number of manycore devices and peak memory on each device; when a new task arrives, querying each node scheduler to determine which node can best accept the task and each node scheduler responds with an estimated completion time and a confidence level, wherein the node schedulers use an urgency-based heuristic to schedule each task and its offloads; responding to an accept/reject query phase, wherein the cluster scheduler send the task requirements to each node and queries if the node can accept the task with an estimated completion time and confidence level; and scheduling tasks and offloads using a aging and urgency-based heuristic, wherein the aging guarantees fairness, and the urgency prioritizes tasks and offloads so that maximal deadlines are met.
Abstract:
Methods and systems for scheduling jobs to manycore nodes in a cluster include selecting a job to run according to the job's wait time and the job's expected execution time; sending job requirements to all nodes in a cluster, where each node includes a manycore processor; determining at each node whether said node has sufficient resources to ever satisfy the job requirements and, if no node has sufficient resources, deleting the job; creating a list of nodes that have sufficient free resources at a present time to satisfy the job requirements; and assigning the job to a node, based on a difference between an expected execution time and associated confidence value for each node and a hypothetical fastest execution time and associated hypothetical maximum confidence value.
Abstract:
A pull-based communication method for microservices-based real-time streaming video analytics pipelines is provided. The method includes receiving a plurality of frames from a plurality of cameras, each camera including a camera sidecar, arranging a plurality of detectors in layers such that a first detector layer includes detectors with detector sidecars and detector business logic, and the second detector layer includes detectors with only sidecars, arranging a plurality of extractors in layers such that a first extractor layer includes extractors with extractor sidecars and extractor business logic, and the second extractor layer includes extractors with only sidecars, and enabling a mesh controller, during registration, to selectively assign inputs to one or more of the detector sidecars of the first detector layer and one or more of the extractor sidecars of the first extractor layer to pull data items for processing.
Abstract:
A computer implemented method is provided for resource management of stream analytics at each individual node that includes computing a mean of output processing rate of microservices in a pipeline; and evaluating a state of each microservice of the microservices in the pipeline. The computer implemented method also includes selecting a single microservice from the pipeline for updating resources for an action that changes the state in single the microservice that is selected; and performing resource allocation update for the selected microservice. The computer implemented method may also include updating the state of the selected microservice.