12 results about "Severity level" patented technology

A method of initiating actions based on analyzing automated fix actions in a telecommunication network management system, the method comprising obtaining, by an incident management application executing on a computer system, prior incident reports associated with a plurality of historical incidents from a database, wherein the prior incident reports comprise one or more recommended corrective actions taken or to be taken to resolve the historical incidents; evaluating, by the incident management application, the prior incident reports to determine a severity level of the prior incident reports and / or an effectiveness value of the one or more recommended corrective actions; prioritizing actions to be taken automatically or by NOC personnel based on the severity level and / or the effectiveness value; and initiating a corrective action to be taken automatically or by the NOC personnel to resolve an active incident report based on the prioritization.

A method of monitoring operation of an aircraft engine includes, during operation of the aircraft engine, monitoring a parameter associated with the aircraft engine using one or more sensors. In response to determining that one or more values of the parameter are indicative of a foreign object damage (FOD) event of a first severity level to the aircraft engine, communicating data pertaining to the FOD event of the first severity level in accordance with a first communication scheme assigned to the first severity level. In response to determining that one or more values of the parameter are indicative of FOD event of a second severity level to the aircraft engine, the second severity level being higher than the first severity level, communicating data pertaining to the FOD event of the second severity level in accordance with a second communication scheme assigned to the second severity level.

The invention discloses a safety operation domain monitoring method for a virtual marshalling train and a related device, and relates to the technical field of rail transit train operation control. Comprising vehicle system related data, signal system data, comprehensive monitoring system data, intelligent operation and maintenance system data and environment sensing data; inputting the safe operation domain state data into the trained safe operation domain situation prediction model to obtain a safe operation domain change trend; inputting the change trend of the safe operation domain into a driving risk propagation model to obtain the probability of occurrence of a driving accident; the driving risk propagation model represents an association relationship between a monitoring index of a safe operation domain and a driving accident; determining a driving risk level according to the occurrence probability of the driving accident and the driving accident consequence severity level; and generating a risk relief strategy according to the driving risk level. Real-time decision support can be provided for the virtual marshalling train, and safe and reliable operation of the virtual marshalling train is ensured.

In some implementations, a compliance system may receive, from a pipeline system, a set of properties associated with configuration of a cloud infrastructure. Additionally, the compliance system may receive, from a code repository, a set of computer code associated with the cloud infrastructure. The compliance system may provide the set of properties and the set of computer code to a machine learning model to receive a set of compliance indicators and a set of severity levels. Each compliance indicator in the set of compliance indicators being associated with a corresponding severity level in the set of severity levels. The compliance system may selectively deploy the cloud infrastructure in response to receiving the set of severity levels.

A system for enhancing personnel safety on a railroad track is presented. The system can receive data from sensors and / or a PTC system to determine positions of clients / worker and / or vehicles, and further utilize such data to determine if a vehicle is within a certain proximity of the client / worker location. The system can further generate geofences around clients / vehicles to and determine when such geofences intersect one another. Additionally, the present disclosure can assign severity levels and generate alerts with the assigned severity levels, and such severity levels can indicate how close a vehicle is to a particular location. It is an object of the invention to provide a system for generating alerts to notify personnel when they much retreat to a place of safety.

In some implementations, a compliance system may receive, from a pipeline system, a set of properties associated with configuration of a cloud infrastructure. Additionally, the compliance system may receive, from a code repository, a set of computer code associated with the cloud infrastructure. The compliance system may provide the set of properties and the set of computer code to a machine learning model to receive a set of compliance indicators and a set of severity levels. Each compliance indicator in the set of compliance indicators being associated with a corresponding severity level in the set of severity levels. The compliance system may selectively deploy the cloud infrastructure in response to receiving the set of severity levels.

The invention relates to an operator station server (OS1.1, OS1.2) for a control system (1) of a technical installation, in particular a manufacturing or process installation, which operator station server is designed to operate and monitor the technical installation and on which at least one software component is implemented, wherein the at least one software component is designed to generate, for the duration of an error occurring in the software component, an alarm having a specified severity level, the severity level of the alarm reflecting the severity level of the error. The operator station server (OS1.1, OS1.2) is characterised in that it is designed to calculate its own health index which depends on the duration and the severity level of the generated alarm, and to transmit this health index to components of the control system (1) that are connected to the operator station server (OS1.1, OS1.2).

The invention discloses a project risk level evaluation method, device and equipment and a storage medium, and the method comprises the steps: inputting obtained project basic information into a prediction model, so as to obtain a risk severity level of a target engineering project; determining a target risk event occurring in the target engineering project from a fault tree, and obtaining a risk coefficient of the target risk event from the fault tree; fusing the risk severity level and the risk coefficients of all the target risk events to obtain a comprehensive risk level of the target engineering project, and performing early warning; according to the invention, the objectivity of the overall risk assessment of the target engineering project can be improved, and the overall risk condition of the target engineering project can be early warned more accurately.

Methods for assessing traffic accidents, characterized by the following features: - Past traffic accidents are recorded, each with a known severity level, and - A model is trained by pairwise differential learning based on past traffic accidents and their respective severity levels to determine the probability with which a simulated traffic accident reaches that severity level for each severity level.

In some implementations, a compliance system may receive, from a tracking system, a set of data structures representing a set of security vulnerabilities and indicating a corresponding set of severity levels. The compliance system may determine a set of levels of effort, corresponding to remediating the set of security vulnerabilities. The compliance system may provide the set of levels of effort to a machine learning model, in order to generate a proposed change to a set of users that are responsible for remediation, and may output an indication of the proposed change. The compliance system may provide the corresponding set of severity levels and the set of levels of effort to the machine learning model in order to generate clusters for the set of security vulnerabilities. The compliance system may output, based on the clusters, an indication of which users are assigned to which security vulnerabilities.

Systems and methods for screening and scoring outputs generated by artificial intelligence language models, including receiving a generated output generated by an artificial intelligence language model in response to a user query, analyzing the output using detection engines, each detection engine evaluating different error dimensions, classifying each detected error into a severity level, generating color-coded visual indicators that correspond to a highest severity level among the one or more detected errors, generating remediation guidance configured to remediate at least one detected error of the one or more detected errors, and presenting screening results including the color-coded visual indicator a list of the one or more detected errors with their respective severity levels and locations, and the remediation guidance.

A system, method, and communication protocol for providing warning indicator severity diagnoses and alerts. The system captures data associated with operations of the vehicle using the plurality of system sensors. The system further detects a service trigger event based on the data that is captured. The system further identifies one or more vehicle components associated with the service trigger event. The system further estimates one or more severity levels of the service trigger event based on the one or more vehicle components that are identified. The system further transmits one or more service alerts to one or more target recipients based on the one or more severity levels for each vehicle component of the one or more vehicle components that is identified in response to at least one severity level of the one or more severity levels meeting a predetermined severity threshold.