WHP Workflow Solutions, Inc.

A system includes a memory circuit configured to store input data, a storage circuit connected to the memory circuit, and a processor connected to the memory circuit and the storage circuit, the processor configured to perform following operation to the input data: receiving the input data in a hierarchical data format from an evidence system, parsing the input data to multiple elements, mapping the multiple elements into multiple fields in a data managing system according to a timestamp table, mapping the input data into an evidence management category according to the multiple fields to generate an evidence management data, and storing the evidence management data with the evidence management category into the storage circuit.

A case management method including steps of providing an incident data, receiving evidence files from a plurality of sources, where each of the evidence files is associated with a metadata; identifying the evidence files based on temporal parameters and spatial parameters, determining a graph structure among the evidence files based on the metadata, where the graph structure includes vertices representing the evidence files and edges representing relationships among the evidence files, and storing the evidence files and the graph structure to an evidence database.

The method for access control to electronic files includes: receiving an access request for an electronic file, the access request includes permission for an access category, the electronic file associated with file categories, and each of file categories associated with a first type or a second type of authority; determining whether any of file categories is associated with the second type of authority; and responsive to one of the file categories associated with second type of authority: determining whether the access category is associated with the second type of authority; responsive to the access category not associated with second type of authority, sending a first access rejection, otherwise determining whether the access category is a same category as the one of the file categories; and responsive to the access category is same category as one of the file categories, sending an access grant, otherwise sending a second access rejection.

A real-time remote troubleshooting system is communicatively connected to a device and a remote console. The real-time remote troubleshooting system includes a memory and a processor. The memory is configured to store instructions. The processor is electrically coupled to the memory and is configured to execute the instructions to: receive a request for remote access to the device from the remote console; provide the remote console with the remote access to the device based on the request; collect logs associated with the device; display the collected logs on the remote console; display information associated with the device on the remote console; and perform an action based on a feedback from the remote console, wherein the feedback is generated corresponding to the collected logs and the displayed information.

Incoming sensor data from a data collection device may be received at the data processing platform that includes the plurality of data processing microservices. A data processing microservice of the data processing platform may detect that the incoming sensor data from the data collection device caused an error. As a result, the incoming sensor data may be queued in a faulty data cache of the data processing platform. Subsequently, at least one of the data processing microservice or the incoming sensor data stored in the faulty data cache may be modified such that the incoming sensor data is processed by the data processing microservice without the error. Following the processing, the incoming sensor data may be deleted from the faulty data queue of the data processing platform.

Operational states of multiple user devices may be managed based on information that is exchanged by the multiple user devices via heartbeat signals. A user device may receive heartbeat signals from multiple connected devices. A determination is made based at least on the heartbeat signals whether a higher-level hub device with an active network connection to a backend service is connected to the particular user device. Thus, in response to determining that no higher-level hub device with an active network connection to the backend service is connected to the user device, a network connection may be established via a communication channel between the particular user device and the backend service.

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.

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.

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).

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).