344 results about "Remote computing" patented technology

A method of operating a device that interacts with a physical environment includes determining to take an action on the physical environment wherein the action is based on an output of a computing task, generating a risk level that estimates a risk of physical harm associated with taking the action within the physical environment, obtaining a performance indicator of a communication network between the device and a remote computing device, and determining, based on the risk level and the performance indicator, whether to offload the computing task to the remote computing device or to perform the computing task locally. Related devices are also disclosed.

Described herein are techniques and mechanisms for geographic routing. A database system may store data records corresponding with user accounts and including historical routing information characterizing geographic routes determined in association with the user accounts. A communication interface may receive a request from a remote computing device authenticated to a user account and identifying an initial geographic location and a terminal geographic location. A geographic routing engine may determine a route including turn-by-turn instructions for moving from the initial geographic location to the terminal geographic location. A generative language model interface may complete a navigation prompt to include novel text identifying supplemental route information. A user interface generation interface may transmit an instruction to the remote computing device to present a user interface that includes the turn-by-turn instructions and some or all of the supplemental route information.

A system for criteria evaluation can include a memory device, a data processing platform with an evaluation engine, and a human interface device. The system can include a processor coupled to the memory device and connected to a remote computing device and to the data processing platform. The processor can be configured to receive an execution request and input data, to convert the input data into a first data format to generate a first data file, as well as to cause the evaluation engine to process the first data file by converting a plurality of subsets of data items into a corresponding plurality of sets of parameter values, to generate a set of scores and a message for the scores, to generate a file having a representation of the scores, and corresponding messages, to present the converted file on a user-interface device.

A system for managing a guardrail data structure is provided. The system includes one or more processors; and one or more transitory or non-transitory computer-readable media storing instructions that are executable to cause the one or more processors to perform operations, the operations comprising: receiving, from a first user of a plurality of users of a guardrail data structure, interaction data associated with chat data; processing, by a large language model (LLM), the interaction data to determine an update to at least one cluster membership of at least one content cluster of a plurality of content clusters; transmitting the update of the at least one cluster membership to a remote computing device; and instructing the remote computing device to update the guardrail data structure based on the update to the at least one cluster membership.

System and methods are disclosed relating to cloud edge based anomaly detection. In an example, an edge monitoring node can include a thermal camera to capture a thermal image of equipment that is under monitoring for an an anomaly event. The node further includes a machine learning (ML) model to process the thermal image of the equipment to detect the anomaly event. The node further includes a network interface to communicate the detected anomaly event over a network to a remote computing platform to determine one or more recommendations for proactive maintenance of the equipment.

A system, method and memory for managing remotely stored data is disclosed. The system is configured to provide an agent within a remote computing environment (RCE) with access to data stored on the RCE and custom applications. In some examples, the agent has access to one or more tools including aspects of a machine learning tool. Another agent on a local computing environment capable of communicating with the agent is provided. The other agent has access to configuration files. The other agent instructs the agent to execute custom applications based on the configuration files. The other agent receives metadata of the data in response to triggering the agent. The instructions cause the processor to populate, via the other agent, a catalogue of the plurality of data within the remote computing environment based on the received plurality of metadata, and provide the catalogue for display for reviewing the plurality of data.

The present disclosure describes a server computing device configured for receiving from a remote computing device via an application, in response to a low-risk access request to a data resource, a programming call with a URL comprising an second identification data item encrypted from a first identification data item acquired by the remote computing device, obtaining a first context information item associated with the programming call, inputting the first context information item into a machine learning model to generate a second context information item, extracting the second identification data item from the URL, generating a third identification data item by decrypting the second identification data item, retrieving a prestored property data item associated with the third identification data item, and transmitting requested data to the remote computing device if comparing the second context information with the prestored property data item produces a match.

Provided are methods, systems, devices, apparatuses, and tangible non-transitory computer readable media for processing avatar content that can be used in a virtual environment. The disclosed technology can generate optimized semantic segments based on assets comprising meshes and textures associated with avatars. Further, the disclosed technology can generate hierarchical skeletons, deformable mesh models, and facial expressions on facial regions of the mesh models. Further, the compatibility of avatars with a virtual environment can be determined and compatible avatars and granular assets associated with avatars can be sent to remote computing systems that are configured to implement the avatars.

A system includes a processing circuit configured to receive data from a sensor of a vehicle. The data includes one or more operational characteristics including at least one of a first operational characteristic indicating that a concrete mixture is being dispensed via a chute of the vehicle or a second operational characteristic indicating that the concrete mixture has stopped being dispensed via the chute. The processing circuit is also configured to receive a first time stamp responsive to receiving the first operational characteristic. The processing circuit is also configured to provide the first time stamp to at least one of a user device or a remote computing system.

Various implementations include processing, at a client device, an instance of audio data capturing a user voice query using an automatic speech recognition model to generate a sequence of instances of tokenizable query text. In many implementations, one or more instances of the sequence can be transmitted to a remote computing system prior to generating the entire sequence. In a variety of implementations, each instance in the sequence can be processed using a generative model which includes a streaming multi-head attention portion. Responsive output can be transmitted from the remote computing system to the client device, where the client device renders the responsive output to the user. In many implementations, the time between the user speaking the user query and the client device rendering the responsive output is reduced, thus decreasing latency in the system.

Embodiments include a computing system, computing device, non-transitory computer readable medium, and computer-implemented method for automating artificial intelligence (AI) prompting and incident summarization. Embodiments provide for automatically generating AI prompts based at least in part on incident information, transmitting the AI prompts to a remote computing system on which a large language model (LLM) is implemented, and providing an AI summary of an incident.

A computing device may establish a call with a remote computing device, and may converse with the remote computing device in the call. The computing device may determine one or more candidate replies based at least in part on contextual information associated with the call. The computing device may receive an indication of a user input to select a candidate reply from the one or more candidate replies, and in response to receiving the indication of the user input to select a candidate reply, may send a reply in the conversation corresponding to the candidate reply.

A golf course geofence system includes a remote computing device. The remote computing device is configured to receive a request from a portable device to generate a geofence at a current location of the portable device on a golf course, acquire position data regarding a position of the portable device, and generate the geofence at the current location in response to the request and based on the position data. The request includes at least one of (a) a first request to generate a predefined shape geofence or (b) a second request to generate a freeform geofence.

Techniques for determining information about an event by one or more devices proximate to a roadway are described herein. For example, a device (e.g., a smart road stud) may include an integrated proximity sensor which can detect a static vehicle or a static object on the road. The device may process the sensor data to determine an event type and an event location for events. In some examples, the device can identify other devices in a vicinity of the event (e.g., other smart road studs located on the road), and select devices for performing actions, such as re-routing traffic. In some examples, the device can send sensor data and / or other types of data to other devices, such as an adjacent smart road stud, an edge device, and / or a remote computing device.

A computing system can automatically generate artificial intelligence (AI) prompts based on incident information, transmit the AI prompts to a remote computing system implementing a large language model (LLM) and receive an AI summary of an incident.

The present disclosure provides systems and methods for predictive analytics. For example, a system provided herein includes a data retriever implemented on a first unit configured to communicate over a data network with a second unit, a database coupled to the first unit and configured to store deal data, and a forecast toolkit implemented on a second unit configured to communicate over the data network with a remote computing device. The forecast toolkit may include a future deal manager configured to identify, within enhanced deal information, future open deals; a machine learning engine; a forecast manager configured to union the future open deals with an initial forecast to produce a second initial forecast, the initial forecast constructed by applying the machine learning engine to historical deal information; and a table builder configured to construct a predicted revenue output based on the second initial forecast.

A method for transmitting event data (21), in particular operator event data and / or status event data, from a field device (2) to a remote computing unit (3), comprising the steps of: generating the event data (21) by means of the field device (2) based on an event; providing an availability signal (22b) indicating the availability of the event data (21) for transmission (32) via a digital communication interface (15) to the remote computing unit (3); and providing the event data (21) for transmission via the digital communication interface (15) to the remote computing unit (3), wherein the event data (21) is provided separately from the availability signal (22b). The method comprises a computer program product, a field device (2) for executing the foregoing method, and a system (1) with the field device (2).

One or more unmanned or remotely controlled flying devices (a / k / a “drones”) are utilized as part of a parking management system to capture images and / or video for the purposes of recognizing vehicles located in parking (or no parking) locations. The image data is relayed to a remote computing system that can be is programmed to specifically identify a vehicle based upon its license plate and / or and unique characteristics of the vehicle (Handicap Placard, Parking Stickers, Make, Model, Color, Registration Stickers, etc.). This information is used to determine if the vehicle has the appropriate credentials to be parked at its location and to assess any parking charges and / or fines for violations. Images from satellites can be used to determine locations to image with the drones.

A clock device is in communication with a remote computing device that is configured to adjust the time of a countdown and define an adjusted time value. The remote device communicates the adjusted time to the clock device, which automatically displays the adjusted time on a screen. The adjusted time is further communicated to a cloud server via API. The adjusted time is accessible by authorized third parties for display or broadcast. Accordingly, a user may adjust and track a countdown and may define an official time that is automatically displayed to a variety of end-users in real-time. The clock device may be positioned adjacent a competition area and may include a rigid metal frame and a flexible LED screen extending around the perimeter of the frame. The clock device may include hardware and software for processing and outputting the adjusted time to the cloud server.

Described embodiments provide systems and methods of providing accessing to a file. A client device may store a copy of a file. The copy may be generated during active use of the file in which content of the file is accessible by the client device via an application hosted on a remote computing device. Responsive to a loss in connectivity that disrupts the active use of the file, the client device may identify a local application on the client device based at least on a type of the file. The client device may use the identified local application to access the copy of the file stored on the client device and continue the active use of content of the file. Subsequent to restoring the connectivity, the client device may provide the file to the remote computing device for synchronization of the file.

To provide a head-mounted display (HMD) for use in a virtual reality (VR) environment in which a user can view the real world without removing the head-mounted display.SOLUTION: The HMD104 includes a display 108 for providing virtual content and / or images to the user 100 and image capture devices, such as the first camera 110 and / or the second camera 112. The first camera 110 and / or the second camera 112 are disposed in or near the front of the MD104 to capture images of the surroundings 102 and pass through the images of the surroundings to the user for viewing on the display. The environment 102 includes a computer 150 that communicatively couples to the HMD, the controller 106, the tracking system 122, and / or the remote computing resources 142 via a network 124 and / or wired technologies.SELECTED DRAWING: Figure 1

A gas monitor includes a housing defining a first flow channel and a second flow channel with a gas sensing element fluidly coupled to each, and each channel including a flow path axis wherein the axes intersect at an angle of at least 60 degrees. Gas monitors can be stacked by engaging a support assembly of one with an engagement assembly of another such that a center of mass of two stacked gas monitors is positioned within a footprint of the support assembly of a lower one of the two stacked gas monitors. The gas monitor includes a battery assembly comprising a plurality of slots configured to each receive a battery pack, however, the gas monitor is configured to operate normally with power provided by a single battery pack. A controller can be configured to operate multiple gas monitors, along with a remote computing device, as a cooperative monitoring group.

A system for the monitoring of plunger lift systems within an oil and gas well, the system may include an acoustic sensor securable to at least a portion of an external surface of a wellhead portion, a transmitter communicatively coupled to the acoustic sensor, and one or more batteries configured to provide electrical power to the acoustic sensor and the transmitter. The monitoring system may measure acoustic vibrations from the internal mechanism of oil and gas equipment with the acoustic sensor and may transmit the acoustic vibration measurements with the transmitter. The transmitted acoustic vibration measurements may be received by a vehicle stereo and reproduced by the speakers of the stereo, or the acoustic vibration measurements may be received by local or remote computing devices. Acoustic vibration measurements may be used to enable the tuning of one or more performance factors for the oil and gas equipment.

The invention relates to the technical field of industrial heat treatment equipment control, in particular to a heat treatment furnace safety control system based on a cloud platform. The multi-dimensional state sensing module is used for collecting real-time physical field data of an industrial controlled object; the signal orthogonal decomposition module is used for decoupling the original state data set into a low-frequency control signal flow and a high-frequency characteristic signal flow, and transmitting the high-frequency characteristic signal flow to a remote computing platform; the state reconstruction module is used for resolving a theoretical state value at the current moment and constructing a virtual sensor observation state; the dynamic envelope generation module is used for calculating a residual error between a theoretical state value and real-time physical field data and generating a dynamic security envelope threshold value and a confidence coefficient attenuation coefficient; and the self-adaptive safety judgment module is used for generating a final safety execution threshold value and executing safety interlocking control on the industrial controlled object. According to the method, the sensitivity of capturing the abnormal working condition in the heat treatment process is improved, and the problem that the static threshold value easily generates false alarm or missing alarm under the complex variable working condition is solved.

A vehicle can connect to multiple vehicles and can determine network metrics (e.g., available bandwidth, latency, signal strength, etc.) associated with the multiple vehicles and at least one cellular network. As the vehicle traverses an environment, the vehicle can collect sensor data of the environment and / or vehicle data (e.g., vehicle pose, diagnostic data, etc.). Based on the network parameters, the vehicle can optimize the use of the connection with the multiple vehicles and / or the cellular network to transmit the sensor data and / or the vehicle data to a remote computing device.

Systems and methods for increasing accuracy in an online chat interface are provided. Methods may be executed via a machine-learning (ML)-based chat monitoring engine. Methods may include intercepting a request utterance. Methods may include computing, via a trained ML model, an intent of the request utterance; generating a target response to the request utterance; intercepting a response utterance; and calculating a difference between the response utterance and the target response. In response to the difference being less than a threshold difference, methods may include releasing the response utterance to be transmitted as a response message. In response to the difference being more than a threshold difference, methods may include preventing the response utterance from being transmitted as a response message, generating a revised response utterance that is less than a threshold difference apart from the target response, and transmitting the revised response as a response message to a remote computing device.

In one aspect, a user's intent can be inferred based on voice analysis during a communications session, and prompts can be presented, or other actions taken, at least partly in response to the inferred intent. For example, a network microphone device (NMD) having one or more microphones can capture voice input and transmit the voice input to remote computing device(s) for a communication session (e.g., a videoconference). The NMD can analyze the voice input to detect one or more utterances. Based on the utterance(s), the NMD can cause a user prompt to be displayed via a display device communicatively coupled to the NMD. The particular prompt can depend at least in part on one or more context parameters associated with the communication session (e.g., a microphone state of one or more users, a screen share state of one or more users, or a recording status of the session, etc.).

The utility model provides a laser gas telemetering system based on remote calculation and control, which comprises a laser receiving and transmitting optical path passing through target gas, and a semiconductor laser and an aiming laser in the laser receiving and transmitting optical path are connected with a laser driving module. A detection laser beam emitted by the laser receiving and transmitting optical path penetrates through target gas and then is transmitted to the photoelectric conversion module, the laser driving module and the photoelectric conversion module are both connected with the data conversion and communication module, and the data conversion and communication module is connected with the remote calculation and control module and the display alarm module. According to the utility model, a wireless data communication technology, a remote calculation and control technology, a tunable laser absorption spectrum technology and a laser remote measurement technology are fused, the problems of high false alarm rate, slow data calculation and the like of the existing detection system are solved, and the monitoring and early warning requirements of high detection speed, high detection precision and few false alarms are met.

A server comprises a communications module; a processor coupled with the communications module; and a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to provide, via the communications module and to a remote computing device, a signal causing the remote computing device to display an interface of a digital wallet management application, the interface allowing one or more digital wallets to be selected; receive, via the communications module and from the remote computing device, a signal indicating a selection of the one or more digital wallets; receive, via the communications module and from the remote computing device, a signal indicating a request to push account information to the selected one or more digital wallets; and send, via the communications module and to one or more servers associated with the one or more digital wallets, a signal configuring the one or more servers to add the account information to the one or more digital wallets.

Described herein is a system and a method for collaborative training of a machine learning model for pose estimation. The system includes a remote computing device in communication with a local computing device, wherein the remote computing device is configured to instruct the local computing device to receive a first image; and generate a first pose datum as a function of the first image using a local machine learning model. The remote computing device is configured to receive, from the local computing device, the first pose datum; generate a second pose datum as a function of the first pose datum and the first image using a remote machine learning model; and configure the local computing device to retrain the local machine learning model as a function of the second pose datum.