54 results about "Critical event" patented technology

Analytics dashboards for critical event management systems that include artificial-intelligence (AI) functionalities, and related software. AI functionalities disclosed include pattern recognition and predictive modelling. One or more pattern-recognition algorithms can be used, for example, to identified patterns or other groupings within stored critical events, which can then be used to improve response performance and / or to inform the generation of predictive models. One or more predictive-modeling algorithms can be used to generate one or more predictive models that can then be used, for example, to make predictions about newly arriving critical events that can then be used, among other things, to provide optimal response performance and allow users to efficiently and effectively manage responses critical events. These and other features are described in detail.

This disclosure describes systems, methods, and devices related to priority packet optimization. For example, a system is described for sideband communication in a universal chiplet interconnect express (UCIe) environment. The system may include a sideband link may include a clock pin and a data pin configured to transmit auxiliary signals between chiplets. The system may include an encoding module configured to generate level-based encodings representing global event notifications. The system may include a notification propagation module configured to distribute global event notifications across a network topology interconnecting the chiplets.

The embodiment of the invention relates to the technical field of communication, in particular to a beam report reporting method and a communication device, which can report beam reports associated with a plurality of events based on a priority rule, not only can avoid the problems of uplink resource competition and signaling conflict caused by simultaneous reporting, but also can improve the user experience. And the problem that the processing of the key event is delayed due to reporting according to a random sequence can also be avoided. The method comprises the following steps: detecting that a plurality of events are triggered, and reporting beam reports associated with the plurality of events according to a priority rule; wherein the priority rule is related to at least one of the following: the type of the triggered event; the triggered event corresponds to the type of the cell.

Analytics dashboards for critical event management systems that include artificial-intelligence (AI) functionalities, and related software. AI functionalities disclosed include pattern recognition and predictive modelling. One or more pattern-recognition algorithms can be used, for example, to identified patterns or other groupings within stored critical events, which can then be used to improve response performance and / or to inform the generation of predictive models. One or more predictive-modeling algorithms can be used to generate one or more predictive models that can then be used, for example, to make predictions about newly arriving critical events that can then be used, among other things, to provide optimal response performance and allow users to efficiently and effectively manage responses critical events. These and other features are described in detail.

Monitoring systems and methods for use in security, safety, and business process applications utilizing a correlation engine are disclosed. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by a correlation engine, optionally by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest, or one or more critical events of interest. Finally, one or more actions are triggered based on a detection of one or more correlations of interest, one or more anomalous events, or one or more critical events of interest. A hierarchical storage manager, having access to a hierarchy of two or more data storage devices, is provided to store data from the one or more sensors.

The present disclosure provides live event systems having one or more processors coupled to memory. The live event system can access a plurality of messages associated with a live event broadcasted to a plurality of broadcast receiver devices via a broadcast provider system. The live event system can determine that at least one message of the messages satisfies a condition of a notification generation policy relating to the live event. The live event system can identify, from the broadcast receiver devices, a subset of broadcast receiver devices that satisfy a notification transmission policy relating to the live event. The live event system can transmit instructions to the broadcast provider system, instructions causing the broadcast provider system to communicate with each broadcast receiver device of the subset of broadcast receiver devices and cause each broadcast receiver device of the subset to display a notification identifying the live event.

The invention discloses an emergency event pre-judgment method, system and device based on a big data model and a storage medium, and relates to the field of big data processing. The method comprises the following steps: acquiring first data of a social network and second data of a government agency; inputting the first data into a preset sentiment analysis model to obtain a sentiment tendency and a sentiment change, and determining a first probability of a current emergency event according to the sentiment tendency and the sentiment change in combination with the second data; when the first probability is greater than a first threshold value, determining a first type and a first geographic position of the critical event, and sending alarm information to a government corresponding department; when the first probability is smaller than or equal to a first threshold value, obtaining a second probability of occurrence of the critical event in future preset time through a preset prediction model; and when the second probability is greater than a second threshold value, predicting a second type and a second geographic position of the critical event, and sending prompt information to a corresponding government department. By implementing the technical scheme provided by the invention, the accuracy of pre-judgment of the emergency event is improved.

This disclosure describes techniques and mechanisms for intelligently sampling packet flows within a network. The techniques enable the sampling of a limited set of packet flows that show greatest amount of information about the network from the packet flows in order to provide the greatest insight on application performance, network packet, and critical events within the network. Additionally, the techniques provide configurable parameters, such that the techniques are customizable for each user's network.

The present disclosure provides a key event analysis method, device and electronic equipment, relates to the technical field of video event analysis method, and solves the problem that in the prior art, the corresponding key event can be marked only after the information to be analyzed is viewed one by one by the viewer when the key event is analyzed, resulting in low key event analysis efficiency. The method comprises the following steps: acquiring a first time sequence feature pool of a first video interval of a to-be-processed video and target data flow; acquiring a second time sequence feature pool in the target data flow based on the first time sequence feature pool; determining a second video interval based on the second time sequence feature pool; and determining a target video interval corresponding to a key event in the to-be-processed video based on the first video interval and the second video interval.

Methods and systems for improved impact detection in a device, such as a head-wearable device, are disclosed. The methods and systems relate to accurately detecting impact events such as falls or vehicular crashes to reduce false positives and enable a swift, appropriate emergency response. A method includes detecting use of the device by a user, for instance, confirming that a head-wearable device is being worn. The method further includes detecting a change in at least one of an orientation or a movement of the device within a threshold time period. An impact is then determined based on the confirmed use of the device and the detected change in its orientation or movement. This approach distinguishes genuine emergencies from non-critical events like dropping the device, thereby improving accuracy and conserving power by intelligently activating additional sensors only when a potential impact is detected.

A computer-implemented method is provided for reinforcement learning performed by a processor. The method includes obtaining, from an environment, a given experience that includes an action, a state and a reward. The method further includes storing the given experience in an experience buffer responsive to a value of the reward included in the given experience exceeding a first threshold. The method also includes responsive to obtaining another experience having another reward that less than or equal to the first threshold, searching the experience buffer for a candidate experience with a similar state to the other experience and copying the candidate experience into an event buffer. The method additionally includes during exploration, selecting an action to be taken to the environment from the event buffer with a predetermined probability.

Systems, computer program products, and methods are described herein for determining and prioritizing interruption events to improve computer processing and performance in an electronic network. The present invention is configured to identify at least one interruption event; apply the at least one interruption event to a stochastic diffusion search (SDS) engine; determine, by the SDS engine, a number of computing agents; analyze the at least one interruption event by the number of computing agents; update, by the number of computing agents, at least one agent priority state for the at least one interruption event; apply the at least one agent priority state to a diagnostic inference model (DIM); and determine, by the DIM, whether the at least one interruption event is a critical event, a non-critical event, or a false event.

Aspects of the present disclosure configure a system component, such as memory sub-system controller, to capture debugging information in memory sub-system operations in response to a critical event. The memory sub-system controller receives critical event trigger data and determines whether the critical event trigger data corresponds to a fatal condition. The memory sub-system controller selects an error handling mode from a plurality of error handling modes based on determining whether the critical event trigger data corresponds to the fatal condition. A first of the plurality of error handling modes corresponds to storing a first set of debugging information associated with a memory sub-system. A second of the plurality of error handling modes corresponds to storing a second set of debugging information associated with the memory sub-system without interrupting a host. The second set can be a subset of the first set of debugging information.

A method for controlling a robotic apparatus. The method includes ascertaining a domain of observations made during subcritical events, from observations of controls from a control data database; ascertaining a criterion using which a limitation of the probability of occurrence of a critical event can be inferred from a limitation of the probability of occurrence of a subcritical event; ascertaining further observations when controlling the robotic apparatus, and ascertaining a relative frequency of those of the further observations that are in the ascertained domain; checking whether the ascertained relative frequency corresponds to a probability of occurrence of a subcritical event that is limited in such a way that a limitation of the probability of occurrence of a critical event can be inferred therefrom according to the criterion; and triggering a safety measure in response to the ascertained frequency not corresponding to a probability of occurrence of the subcritical event.

For deployed products containing Al models, environmental effects or failures may occur that cause the Al to detect an event that is not recognized. In these cases, it may be necessary to identify the nature of the event that triggered the Al process to output an unknown or anomalous event. This can be difficult as the product may be in operation and deployed for use in a residential or commercial setting. By identifying the nature of the event, and labeling it along with the associated data, the Al model can be retrained to allow it to properly recognize these events in the future. To facilitate this a smart phone application is disclosed that provides connectivity to critical event information, to event labeling, and to the model retraining process.

According to various embodiments, a method for controlling a robot device is described, comprising: determining, from observations of controllers from a control data database, a range of observations made during subcritical events; determining a criterion by means of which a limitation of the probability of occurrence of a subcritical event can be used to infer a limitation of the probability of occurrence of a critical event; determining further observations during the control of the robot device and determining a relative frequency of those of the further observations that lie within the determined range; and verifying whether the determined relative frequency corresponds to a probability of occurrence of a subcritical event that is limited in this way.that, according to the criterion, a limitation of the probability of occurrence of a critical event can be inferred from this, and triggering a safety measure in response to the fact that the determined frequency does not correspond to a probability of occurrence of a subcritical event that is limited in such a way that, according to the criterion, a limitation of the probability of occurrence of a critical event can be inferred from this.

Techniques are set forth for dynamically generating media content clips based on key events occurring. Specifically, these techniques enable identification of key events in event streams occurring in the real world (e.g., at reward events, social events, at sporting events, etc.), and enable dynamic generation of media content clips for the key events. In turn, the key event and its corresponding media content clip may be presented to a user for viewing.

Aspects of the present disclosure configure a system component, such as a memory subsystem controller, to capture debug information in memory subsystem operations in response to a critical event. The memory subsystem controller receives critical event trigger data and determines whether the critical event trigger data corresponds to a fatal condition. The memory subsystem controller selects an error handling mode from a plurality of error handling modes based on determining whether the critical event trigger data corresponds to the fatal condition. A first one of the plurality of error handling modes corresponds to storing a first set of debug information associated with the memory subsystem. A second one of the plurality of error handling modes corresponds to storing a second set of debug information associated with the memory subsystem without interrupting the host. The second set may be a subset of the first set of debug information.

Analytics dashboards for critical event management systems that include artificial-intelligence (AI) functionalities, and related software. AI functionalities disclosed include pattern recognition and predictive modelling. One or more pattern-recognition algorithms can be used, for example, to identified patterns or other groupings within stored critical events, which can then be used to improve response performance and / or to inform the generation of predictive models. One or more predictive-modeling algorithms can be used to generate one or more predictive models that can then be used, for example, to make predictions about newly arriving critical events that can then be used, among other things, to provide optimal response performance and allow users to efficiently and effectively manage responses critical events. These and other features are described in detail.

This invention relates to a real-time early warning method and system for abnormal physiological states based on critical events during flight, belonging to the field of aviation medical diagnosis and identification. It addresses the problems of insufficient automated identification of critical events and the lack of real-time early warning of pilot physiological states in existing simulated flight training. The method includes acquiring flight parameter data and physiological parameter data of the pilot during simulated flight; acquiring the pilot's resting baseline physiological parameter data; calculating energy quantification indicators based on the flight parameter data during simulated flight; identifying the types of critical events during simulated flight based on the flight parameter data and energy quantification indicators; and identifying the pilot's physiological state based on the physiological parameter data, resting baseline physiological parameter data, and types of critical events during simulated flight, and issuing real-time early warnings if abnormalities are detected. This achieves real-time early warning of abnormal physiological states of pilots in the air.

This invention relates to the field of quality traceability technology in the chemical industry, providing a method and system for resolving emulsifier quality traceability identifiers throughout the entire process. The method includes: generating carrier identifiers resistant to physical corrosion for raw materials; real-time sensing of critical events in emulsifier phase transitions using a multi-mode sensor array deployed on production equipment; automatically triggering the generation of derived identifiers associated with the previous identifier when a preset phase transition condition is detected; dynamically binding key process parameters and quality inspection data from the production process to the identifiers of the current stage after aggregation through edge computing nodes; and storing summary information of the identifiers and their associated data from each stage in a cross-enterprise blockchain consortium network to form an immutable traceability chain. This invention ensures the continuity of identifiers throughout the physical evolution process and achieves reliable interaction and efficient resolution of cross-system data.

The invention relates to an operation threat detection system and method for mobile assets, and the system comprises a mobile asset airborne data collection and recording system, the system includes an event detector, a gyroscope, a global positioning system, and a digital video recorder adapted to receive data obtained from at least one of onboard at least one mobile asset and off-board of the at least one mobile asset; and a processing component adapted to obtain at least one media file from the at least one mobile asset and process the at least one media file to determine threat detection, critical event detection, and non-compliance applicable mobile asset regulations.

A computer system receives, by an interface agent and via a web user interface, a first user query from a user that defines a request to summarize historical data corresponding to a critical event associated with a plurality of computing incidents. In response to receiving the first user query, the computer system instantiates, by an executing agent, an event report associated with the critical event. The computer system displays the event report to the user. The computer system receives, by the interface agent and via the web user interface, a second user query from the user that defines a request to reduce a mean time to repair (MTTR) for resolving the critical event. In response to receiving the second user query, the computer system instantiates, by the executing agent, an enhanced standard operating procedure (SOP) configured to reduce the MTTR. The computer system displays the enhanced SOP to the user.

Systems and methods are disclosure for using sensors to deliver educational content to vehicle users during critical events. One method comprises: receiving, by a first computing device having at least one processor and from a user device of a vehicle user via a wireless data connection, a notification of a critical event for a vehicle of the vehicle user and a vehicle identification of the vehicle; receiving, from the user device via the first wireless data connection, user input soliciting educational content to remedy the critical event; determining, based on the received user input, a first set of search parameters; for each of the search parameters in the first set of search parameters, selecting educational content for a first list of educational content from a second list of educational content; and displaying, on the user device, the first list of educational content based on the first set of search parameters.

Various embodiments described herein relate to providing and / or employing a system and a method for tracking incoming events in a facility. In this regard, event data associated with a plurality of events is collected from at least one data source of a plurality of data sources. As a result, duplicate events are identified and filtered out from the plurality of events. Further, a set of anomalous events from the plurality of events is identified after filtering out the duplicate events. In this regard, at least one throttling parameter is adjusted in real-time based on the identification of the set of anomalous events and a current load on the system. Accordingly, processing of critical events from the set of anomalous events is prioritized based on the adjusted at least one throttling parameter.

The present disclosure provides live event systems having one or more processors coupled to memory. The live event system can access a plurality of messages associated with a live event broadcasted to a plurality of broadcast receiver devices via a broadcast provider system. The live event system can determine that at least one message of the messages satisfies a condition of a notification generation policy relating to the live event. The live event system can identify, from the broadcast receiver devices, a subset of broadcast receiver devices that satisfy a notification transmission policy relating to the live event. The live event system can transmit instructions to the broadcast provider system, instructions causing the broadcast provider system to communicate with each broadcast receiver device of the subset of broadcast receiver devices and cause each broadcast receiver device of the subset to display a notification identifying the live event.

Systems and methods are disclosed for using a hub to automate recovery. One method may include, receiving, a notification of a critical event, first vehicle information of a first vehicle associated with the critical event, and second vehicle information of a second vehicle associated with the critical event; receiving, first damage information related to the critical event; analyzing, the second vehicle information to identify the second vehicle; determining, a second user device associated with the second vehicle; establishing, communication with the second user device; transmitting to the second user device, a request for input wherein the input is second damage information related to the critical event; receiving, the second damage information; comparing the first damage information to the second damage information; generating, a response certainty score based on the comparison; determining, that the response certainty score satisfies a confidence value threshold; and determining, a fault assessment for the critical event.

The present invention relates to a method for identifying pipeline failures that enables the detection of specific failures in critical events, since it presents an optimized search space for obtaining a precise and adaptable trained model, based on the use of a hybrid database comprising operational data and simulated data, and feedback from performance metrics combining variable data in an optimizer, generating machine learning models with greater specialization capacity and consequently allowing an increased capacity for classifying critical events.

The embodiment of the invention provides an interaction method and related equipment / products, and relates to the technical field of artificial intelligence. The interaction method comprises the following steps: determining whether a moving object exists in a target environment at the current moment; under the condition that the moving object exists, an information event at the current moment is obtained, and an interaction event of the moving object for the target environment at the current moment is determined; determining respective effective information amounts of the information event and the interaction event according to the moving object, and determining the information event or the interaction event as a target event based on the effective information amounts; and determining target interaction content based on the target event, and presenting the target interaction content to the moving object. According to the technical scheme, the event most critical to the moving object in a complex scene can be accurately recognized, and the interaction content matched with the requirement of the moving object is selected and presented according to the key event, so that the man-machine interaction effect is remarkably improved.

The application provides a drought-flood sudden change key factor prediction method and system based on causal inference, relates to the drought-flood sudden change prediction technical field, and comprises the following steps: acquiring critical state data of a drought-flood system when the drought-flood system transits from a metastable state to a sudden change state; determining a critical starting point of drought-flood sudden change; screening a precursor factor of an order parameter capable of driving the system to transit from a metastable state to a critical state; excluding a pseudo factor that only accompanies a critical state but has no driving effect; verifying the universality of each factor in a candidate factor set in triggering a critical phase change of the system; screening a factor with cross-system domain universal driving performance and determining the factor as a drought-flood sudden change key factor; constructing a critical phase change deduction model; predicting whether the system will have a critical transition in the future 1-15 days and generating a prediction report. By means of a critical state fingerprint matching method, multi-dimensional core fingerprint characteristics are extracted, the critical starting point of drought-flood sudden change can be accurately determined, a complete critical state event list associated with geographical environment information is generated, and the accuracy of critical event identification is improved.