Whp Workflow Solutions, Inc.

Getac Technology Corporation

Getac Corporation

Getac Holdings Corporation

Muhammad Adeel

Thomas Guzik

Ryan Kucera

In multimedia object tracking and merging of tracked objects, an object is tracked through frames of multimedia content until a frame appears in which the tracked object is not detected. A first track is designated as one or more consecutive frames in which the tracked object is detected, the first track ending at the first frame. Tracking continues to try to detect the tracked object in a second frame subsequent to the first frame. If the tracked object is not again detected, information about the first track is output. If the tracked object is detected subsequently, a second track of consecutive tracked object detection is designated. The tracked objects in the two tracks are then compared with the aid of trained data models, and a matching score is determined to reflect the degree of match. If the matching score meets or exceeds a first threshold, the compared tracks are merged using the same identifier assigned to both tracks. If the matching score does not exceed a second threshold that is less than the first threshold, the tracks may be discarded as showing no match. If the matching score falls between the first and second thresholds, an indication is output for further analysis of the compared tracked objects.

Multimedia object tracking and merging

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, to manage device communications during emergent conditions are disclosed. In one aspect, a method includes the actions of receiving, by a first computing device, data indicating that a second computing device is configured to communicate using a first protocol. The actions include receiving data indicating that a third computing device is configured to communicate using the first protocol and a second protocol. The actions include determining that the second computing device is unable to communicate with a fourth computing device. The actions include determining a context. The actions include generating an instruction for the third computing device to communicate with the second computing device using the first protocol. The actions include outputting, to the third computing device, the instruction for the third computing device to communicate with the second computing device using the first protocol.

Device communication during emergent conditions

This disclosure describes techniques for continuous improvement of machine learning models (also called data models) in a Content Management System (CMS). In one example, a CMS may store a set of data models for each application such as plate number recognition, facial recognition, a determination of likelihood of assault to a law enforcement officer in a traffic violation or robbery scenario, and car identification. In an example embodiment, a predictive model may be used to select a data model from the plurality of data models. The selected data model may be further improved or trained to a new sample of data features to generate an output pattern (e.g., likelihood of assault to a law enforcement officer).

Artificial intelligence (AI) trained data model selection

Image readability is improved via one or more patterns taken using different light wavelengths. A first pattern may include alphanumeric characters, barcodes, Quick Response (QR) codes, or a similar unique code that can be used to identify vehicle license plates, road signals, charts, placards, advertisements, or the like, using a light wavelength such as a visible light wavelength. A paired second pattern may include a copy of the first pattern or a different pattern but constructed with a different material that responds to a different light wavelength e.g., Ultra-Violet (UV) light wavelength. In one example, the paired second pattern may be identified and used as a reference for identifying the first pattern. This technique of using multi-patterns for identifying road signals, charts, placards, advertisements, and particularly the vehicle license plates during extreme weather conditions may improve law enforcement operations or other similar purposes.

Techniques for improving an image readability using one or more patterns

A content management system (CMS) manages content for trained machine learning (ML) models. The CMS may develop first, second, and third trained ML models from corresponding datasets, to output respective values of dependent variables derived from data underlying the datasets as independent variables, the respective outputs having statistical confidences in the accuracy of their predictions. The third dataset results from combining the first and second datasets, and the third trained ML model is derived from training on the third dataset. The datasets and ML models are stored in a data store, with the trained ML models associated with respective datasets, the datasets with respective underlying data, the trained ML models with respective statistical confidences and corresponding thresholds, and the trained ML models with metadata indicating independent and dependent variables. The datasets and ML models can be versioned and the provenance of the datasets tracked for future ML modeling.

Content management system for trained machine learning models

A microservices platform that includes a plurality of microservices for providing data processing functions for data of multiple tenants may be implemented. Each tenant of the multiple tenants may be provided with an assigned binary large object (blob) data store in a blob storage platform that is only accessible by a corresponding tenant using a corresponding tenant identifier. Furthermore, each tenant of the multiple tenants may be assigned a corresponding local database at each microservice of the plurality of microservices that is only accessible by the corresponding tenant using the corresponding tenant identifier.

Maintaining data security in a multi-tenant microservice environment

A video file may be presented via a user application that displays one or more video frames of the video file. A user request to perform an object detection for objects of a specific object type in a video frame of the video file may be received from the user application. A machine-learning model of a plurality of machine-learning models that is configured to detect objects of the specific object type may be applied to the video frame to detect an object of the specific object type in the video frame. Each of the plurality of machine-learning models may be trained to detect objects of a corresponding object type. Subsequently, an object tracking algorithm may be applied to one or more additional video frames of the video file to track the object of the specific object type across the one or more additional video frames.

Systems and methods for tracking objects in videos using machine-learning models

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automated camera activation are disclosed. In one aspect, a method includes the actions of receiving, from a sensor, sensor data. The actions further include, based on the sensor data, determining that a firearm has been removed from a holster. The actions further include, based on determining that the firearm has been removed from the holster, generating a software-recognized event that indicates the firearm has been removed from the holster. The actions further include, in response to the software-recognized event that indicates the firearm has been removed from the holster, generating an instruction for a camera to record. The actions further include providing, for output, the instruction for the camera to record.

Automated camera activation

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, to manage devices during emergent conditions are disclosed. In one aspect, a method includes the actions of receiving, by a first computing device, data indicating a function of a second computing device. The actions further include determining, by the first computing device, a context of the second computing device. Based on the context of the second computing device, the actions further include determining, by the first computing device, whether to activate the function of the second computing device. Based on determining whether to activate the function of the second computing device, the actions further include determining, by the first computing device, whether to output, to the second computing device, an instruction to activate the function.

Device management during emergent conditions

This disclosure describes techniques for implementing an asset bucket on user devices for organizing assets in a database. Assets may include, without limitation, stored multimedia data from various sources, grouped multimedia data, events, conditions, parameters, environmental data, and other data or telemetry data that are stored in a network operating center (NOC) server database or a third-party database. The asset bucket may include a persistent working space that can be rendered as a pane on a device's user interface for organizing assets that can be selected from a rendered window or windows on the device's user interface and/or directly inputted on the persistent working space. By configuring the asset bucket to facilitate performance of actions on the selected assets, the asset bucket may improve generation of reports on these selected assets.

Using an asset bucket for correlating assets

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, to dynamically utilize multiple devices are disclosed. In one aspect, a method includes the actions of receiving, by a first computing device, data indicating a first function of a second computing device. The actions further include receiving, by the first computing device, data indicating a second function of a third computing device. The actions further include determining, by the first computing device, that the first function of the second computing device and the second function of the third computing device perform a same function. The actions further include generating, by the first computing device, an instruction for the third computing device to disable the second function. The actions further include providing, for output by the first computing device and to the third computing device, the instruction for the third computing device to disable the second function.

Dynamic utilization of multiple devices

A communication broker service of a microservices platform may direct a distributed queue management service to monitor multiple data distribution outboxes of a plurality of microservices of the microservices platform for message data. The communication broker service may receive an indication from the distributed queue management service that the distributed queue management service has retrieved message data from a data distribution outbox of a first microservice. The communication broker service may apply a business logic to identify one or more second microservices that are configured to receive the message data from the first microservice. The communication broker server may then direct the distributed queue management service to distribute the message data of the first microservice from a data store of the distributed queue management service to one or more corresponding data distribution inboxes of the one or more second microservices.

Interservice communication optimization for microservices

This disclosure describes techniques that enable a categorization controller to detect activation of a portable recording device that is configured to capture a real-time multimedia stream of the current event. The categorization controller may further identify a set of categories that are likely associated with the real-time multimedia stream, determine an ordered ranking of the set of categories, and generate a ranked category dataset for delivery to the portable recording device. In doing so, the portable recording device may present the ordered ranking of the set of categories at a user interface.

Incident category selection optimization

A system and method for multi-media content bookmarking with provenance supplements multi-media content captured by media recording devices used or carried by a police officer during the course of his/her duties with information inputted by the police officer, wherein the added information is in the form of metadata. In at least one embodiment, a user interface (UI) tool for inputting the supplemental metadata is the source of provenance for the metadata, and the supplemental metadata is tagged to the captured content in a manner that preserves the provenance of the captured content. In a further embodiment, the user interface further enables the officer to create an affidavit as to the veracity of the supplemental metadata. The supplemental metadata may be stored in conjunction with the captured multi-media content in a secure data storage, but the content itself is not altered, thereby maintaining provenance of the content.

System and method for multi-media content bookmarking with provenance

This disclosure describes an apparatus and system for classifying audio and video data captured by a portable recording device. The portable recording device may comprise a camera system enclosure that captures audio and video data that reflects a user's point-of-view perception of their surroundings. The video and/or audio data may be transmitted in real-time, or near real-time, to a Central Multimedia Management (CMM) System at a Network Operations Center, or one or more mobile computing devices, via one or more networks. Alternatively, or additionally, the video and/or audio data may be stored within memory of the portable recording device. This disclosure further describes a CMM system that may act as a central repository of multimedia data from one or more portable recording device(s). The CMM system may further generate and assign incident report forms for each individual instance of real-time data that is recorded by a portable recording device.

Growing community of inventors

Edina, MN, United States of America

Muhammad Adeel