Abstract: System and method for model orchestration and sensor correlation according to certain embodiments. For example, a method includes: accessing a plurality of models, each model of the plurality of models configured to process data; receiving information corresponding to a plurality of sensors associated with a plurality of edge devices; selecting one or more models from the plurality of models based on a processing request; selecting one or more sensors from the plurality of sensors based on the processing request; building one or more model pipelines based at least in part on the one or more selected models and the one or more selected sensors; and deploying the one or more model pipelines.

Abstract: In some examples, systems and methods for mixed reality are provided. For example, a method includes: generating a three-dimensional image based on target area data from one or more first data sources; receiving object data associated with one or more digital objects from one or more second data sources; generating an object representation including a representation of at least one of the one or more digital objects based on the object data associated with one or more digital objects; overlaying the object representation on the three-dimensional image to generate a three-dimensional representation; and projecting the three-dimensional representation including the overlaid object representation via a virtual reality device; wherein the method is performed by one or more processors.

Abstract: The systems, methods, and devices of the present disclosure may provide, among other features, high-performance, interactive geographical and/or data object map capabilities in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. In various embodiments, an interactive geographical map display system may enable rapid and deep analysis of various objects, features, and/or metadata by the user by aggregating and clustering large sets of data into aggregate values and clusters. The user can select various clusters, via the user interface, to interact with the data, clusters, and map.

Abstract: Systems and methods provide synchronizing edge server code among a plurality of edge servers. Systems and methods provision, to a plurality of edge servers, an updated version of transform code adapted to perform real-time processing on real-time streaming data that are received by the plurality of edge servers, receive real-time transformed data from at least one of the plurality of edge servers, detect that the received real-time transformed data from the at least one of the plurality of edge servers was generated using a previous version of transform code and perform one or more transform operations corresponding to the updated version of transform code on the received real-time transformed data, until the received transformed data is in a form consistent with the updated version of provisioned transform code.

Abstract: In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.

Abstract: In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.

Abstract: Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.

Abstract: Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.

Abstract: The systems, methods, and devices of the present disclosure may provide, among other features, high-performance, interactive geographical and/or data object map capabilities in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. In various embodiments, an interactive geographical map display system may enable rapid and deep analysis of various objects, features, and/or metadata by the user by aggregating and clustering large sets of data into aggregate values and clusters. The user can select various clusters, via the user interface, to interact with the data, clusters, and map.

Abstract: The systems, methods, and devices of the present disclosure may provide, among other features, high-performance, interactive geographical and/or data object map capabilities in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. In various embodiments, an interactive geographical map display system may enable rapid and deep analysis of various objects, features, and/or metadata by the user by aggregating and clustering large sets of data into aggregate values and clusters. The user can select various clusters, via the user interface, to interact with the data, clusters, and map.

Abstract: In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.

Abstract: Systems and methods for video georegistration are provided. An example method includes: receiving an input image; generating a plurality of templates from the input image; and generating a template queue based at least in part on the plurality of template scores. The plurality of templates are associated with a plurality of template scores. The template queue includes a set of selected templates. The method further includes receiving one or more reference images; determining a set of match scores for the set of selected templates by applying a matching algorithm to the set of selected templates and at least one reference image of the one or more reference images; evaluating the set of match scores to select a collection of templates, and generating an image transform based at least in part on the collection of templates. Each template of the collection of templates meets one or more selection criteria.

Abstract: Systems and methods for performing sensor correlation by a plurality of edge devices are disclosed. For example, a method includes: receiving a first set of edge data from a first edge device of the plurality of edge devices; receiving a second set of edge data from a second edge device of the plurality of edge devices, the second edge device being different from the first edge device; analyzing the first set of edge data using one or more computing models to determine a first object detected in the first set of edge data; analyzing the second set of edge data using the one or more computing models to determine a second object detected in the second set of edge data; and determining whether the first object and the second object are a same object based upon one or more object parameters.

Abstract: Disclosed herein are systems and methods for sensor cueing. In one example, the method includes: receiving a model inference from a computing model using a first set of sensor data, the model inference associated with a target object; generating a sensor command based at least in part upon the model inference, the sensor command comprising one or more object parameters associated with the target object and one or more sensor parameters associated with a sensor; and transmitting the sensor command to the sensor via a sensor API.

Abstract: Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.

Abstract: Disclosed herein are systems and methods for model selection and update operation. The methods include receiving a model request with parameters selected from a group consisting of a type of computing model, a processing characteristic, and a data characteristic; receiving information associated with a plurality of computing models from a model repository; selecting one or more computing models based upon the model request; compiling a container request based on the model request and the one or more selected computing models; transmitting the container request to a container infrastructure; and coupling the one or more selected computing models to an artificial intelligence inference platform (AIP).

Abstract: In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.

Abstract: Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.

Abstract: System and method for model orchestration and sensor correlation according to certain embodiments. For example, a method includes: accessing a plurality of models, each model of the plurality of models configured to process data; receiving information corresponding to a plurality of sensors associated with a plurality of edge devices; selecting one or more models from the plurality of models based on a processing request; selecting one or more sensors from the plurality of sensors based on the processing request; building one or more model pipelines based at least in part on the one or more selected models and the one or more selected sensors; and deploying the one or more model pipelines.

Abstract: System and method for using and managing artificial intelligence (AI) inference platform (AIP) and/or model orchestrators according to certain embodiments. For example, a method includes receiving sensor data via a data interface of a model orchestrator, the model orchestrator including an indication of a model pipeline, the model pipeline including a plurality of models; loading the plurality of models according to the model pipeline; applying the model pipeline to the received sensor data; receiving a model output from the model pipeline via a model interface of the model orchestrator; and generating an insight based at least in part on the model output.